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Bibliography of the Book Matrix Computations
Original authors: Gene H. Golub
(Stanford University)
Charles Van Loan
(Cornell University)
BibTEX conversion by
Chris Paige
Clement Pellerin
(McGill University)
LaTEX wrapper and prettyprinting by
Nelson H. F. Beebe
Center for Scientific Computing
Department of Mathematics
University of Utah
Salt Lake City, UT 84112
USA
Tel: +1 801 581 5254
E-mail: Beebe@math.utah.edu (Internet)
07 May 1999
Version 1.10

Abstract

sity, Montreal, PQ, Canada H3A 2A7). Send
any corrections by e-mail to to Charles Van
This bibliography is from the book Matrix Loan at cv@cs.cornell.edu.
This wrapper, and the prettyprinting of
Computations, Second Edition, by Gene H.
Golub and Charles F. Van Loan, The Johns the bibliography file, were supplied by Nelson
Hopkins University Press, Baltimore, Mary- H. F. Beebe (University of Utah).
land 21218, 1989.
The master bibliography is available from
the
netlib service; to fetch a copy, send eThe original bibliography was prepared by
mail
to netlib@ornl.gov with the text send
Charles Van Loan (Computer Science, Cornell
gvl.bib
from bib.
University, Ithaca, NY 14583). It was corThis prettyprinted version is available from
rected, edited, and put in BibTEX format in
September 1990 by Chris Paige and Clement the tuglib service; send e-mail to tuglib@Pellerin (Computer Science, McGill Univer- math.utah.edu with the text send gvl.bib
1

Golub and Van Loan: gvl.bib

from tex/bib.

Title word cross-reference
(A − λB)x = 0 [Sch74]. −1 [KW87]. A
[PW69, You72]. A − λB
[Kåg85, Kåg86, TW70]. A = 1 + H [Buc74].
{aij } [Asp59]. aij = 0 [Asp59].
AX + XB = C [BS72, GNL79].
AX − XB T = C [Bye84]. Ax = λBx
[Erd67, GUW72, MW68c, PW69, PW70a,
Rod73, Ste72, Ste75b]. Ay = λBy [TW72].
B [PW69]. ` [Hoc83]. H [Buc74]. ijk
[OR88]. j > i + p [Asp59]. k [NV83]. L1
[BCS78, BR73, CP76]. L2 [GV74]. L∞
[BCC78]. M [Bar87, MdV77].
PN [JH88].
fp (A)Xgp (A)
O(n2 ) [Dor73]. RN [Bjö88].
[WZ72]. kA−1 k [Var76].
- [OS81]. -Cube [JH88]. -Matrix
[Bar87, MdV77]. -Scaling [GV74].
-Solutions [CP76]. -step [NV83].
100 [LV75, NV75]. 10P [DD88].
2 [CDH84]. 200/VF [DD88].
3090 [DD88]. 3090-200 [DD88].
3090-200/VF [DD88].
4 [DH86]. 400 [KL88].
Accelerating [Ste69]. Acceleration [YJ80].
Accuracy [Don83, DMW83, Hig88a, Pai80,
Rob77, Sco85, War77]. Accurate [DK88].
ADI [CMdP84]. Adjoint [GK69].
Advances [Wil77]. after [Ruh69b]. Aid
[LO83]. Algebra
[Bun87, CDH84, DJK+ 88, DCHH88a,
DGK84, DH86, DS86, FF63, FF77, Fox64,
GJM87, GJMS88, Gol74, Hag88, Hel78,
Hig85, Joh87a, Kah66, Kan66, Lau85,

2

LHKK79a, LHKK79b, Leo80, Mir55, ND77,
Str88, Wil77, WR71, DCDH88, DCHH88b].
Algebraic [AL84, Bye83, FM67, Nas75,
Rob77, Wil63, Wil65a, Wil68c, vdS70].
Algebraically [Cul78, CD74]. Algorithm
[AC84, APP88, AL73, AL85, AC76, Bai88a,
BP75a, BR73, BS79, Bjö84, BB71, BG84b,
BG69, Bye86, Cha82a, Cha82b, CD87, CP77,
CVD88, Cra86, CD74, CWL83, Cyb80,
Cyb84, DT71, DCHH88a, DE84, DS87a,
Dub70, DMW68, Eld84, Eld88, FH72,
GJMS88, GPS76a, Gol74, GUW72, Gra86,
Gre81, HL69, Hel76, HP78, Hua81, HV88a,
HV88b, HVH87, JP71, Kåg86, KR80a,
KR80b, Kar74, Kau74, Kau77, Ker82, LH69,
LHKK79a, LPS87, Loa75a, MPW70,
MRW70, MW68b, MP82, MS73b, ML82,
Nan85, O’L80a, Paa71, Pai76, Pai80, PD86,
PS78, PS82a, PS82b, Par65, Par66, Par68,
Par80a, PR81, PS79, PSS82, Ros69, Ruh69a,
Saa82, SS86, Sco79b, SB79, Sim84, Ste70,
Ste76a, Ste79a, Ste85, Sto73, Swa79, Swe74,
Swe77, Tre64, War75, Wat73, Wat82,
Wil68b, Wil79, Win68, Zoh69].
Algorithmic [CdB80]. Algorithms
[AL84, BG76, BS86, Bis88b, BE73, BMRW68,
Bre70, Bud64, Bun87, Bye83, Cal86, CDH84,
CW77, CW85b, CW85a, Cyb78, DGKS76,
DGK84, DH86, DSS86, Doo83, DGR79,
EHHR88, Eld77a, FOH87, GR84, GPS76b,
Hea78, Hel78, Hig86b, Hig87b, JH87a, JH88,
KNP87, KNP88, KP74, Knu81, Kub61,
Lew77, Loa73, Mod88, MvdV87, O’L76,
OS85, Pai81, Par71, Pry85, Ris73, Ruh79,
Sam71, SHW86, Wil65b, Woz80]. Allowing
[SS79]. Almost [Ruh75, Wed73a, Wil68a].
Alternating [CJZ83, JH87b]. Alternative
[MC86]. Among [Par76]. Analogue [Fra61].
Analyses [Mei83]. Analysis
[Abd71, APP88, AL85, Bel70, Bjö87, Bre70,
Bun71a, CdB80, Cyb78, Dem88, Eld77b,
Elm86, FNO87, Gen73a, GL80, Gre52,
HN81, Hig87b, Hig89, Hoa77, Hoc65, Hot57,
Hou74, Huf87, IP87, JO74, KP74, Kie87,

Golub and Van Loan: gvl.bib

Loa83, MS78, MM83, NV83, Ort72, Pai73,
Pai76, Pai79a, Par71, Ple86, Pry85, Sco78,
Sim84, Sor85, Sun83, Var62, Wil61, Wil68c,
Wil71, Woz80, dBP77]. Analyst [Dem83b].
Angles [BG73]. Application
[ES86, FU69, JO71, Kau79, Loa77a, McC72,
Ris73, Sch09, Ste80]. Applications
[AG87, AG88, Bar87, BS68, Fox88, Fra64a,
Fra64b, GLR86, GT81, HL69, Hig86a,
Hig88d, Hig88e, LH69, Leo80, Loa73, Nas76,
Opp78, RW72a, Str88, TG81, Van71, Var73].
Applied [Hag88, HY81, ND77, Ple86].
Applying [PR68]. Approach [CdB80,
Doo81b, HV87, KP81, KM86a, McC72].
Approaching [DH86]. Approximate
[AP86, KPJ82, OP64, Ste71].
Approximating [DGR79, Loa84].
Approximation
[BR73, GHS88, Gre52, Loa77a, Saa86].
Approximations [FL70]. Arbitrary [HS88,
Hua75, JH87a, Lot56, Ruh68, Sch79, Swe77].
Architectures [Bis87, Joh84, Joh85, Joh86,
Joh87b, JH88, Kun82]. Arguments [Var76].
Arising [Saa86, Var72]. Arithmetic
[Gre81, KM86b, Ste81a, Yoh79]. Array
[BL86, KB84, Luk86b, Sch86]. Arrays
[AC84, BL85, ES86, GK82, ST86, SHW86].
Art [IP87]. Aspect [Nic74]. Aspects
[Hel76, Lau85, Ruh79, Ruh83, Rut69].
Assignment [MP82, OS86]. Associated
[HVH87, Ste73b, SW80]. Asymptotic
[Ste84a]. aufzulösen [Jac46]. Augmented
[Cox81]. Automatic [KdV77]. Average
[TS87]. Axis [EY39].
Backward [ADD88, dBP77]. Balancing
[PR69, War81]. Band
[All73, Boh75, CKS78, CS87, Cox81, Cra73,
JO77, Joh86, MRW70, MW65, MW67,
PW69, Rei67, Ruh79, Sch68, Sco84, Tre74].
Banded [DS84, Eld84, Joh85, WAC+ 88].
Bandwidth [Cut72, GPS76a, GPS76b].
Based [Cal86, CW80, HN81]. Basic
[DCHH88a, Joh87a, LHKK79a, LHKK79b,

3

Par68, DCDH88, DCHH88b]. Bauer
[Rut69]. be [Bus68]. Behavior
[Gre81, Ste84a]. Best [BB71, GV74].
Between [AR85, BG73]. Bibliographical
[Ste76b]. Bidiagonalization
[OS81, Pai74a, PS78]. Biharmonic [BD74].
Bilineari [Bel73]. Binary [Ste81a].
Biorthogonalization [Saa82]. Bisection
[BMW67]. Bisectors [Par71]. Björck
[Hig87b]. Björck-Pereyra [Hig87b]. BLAS
[DD88, KL88]. BLAS3 [GJM87]. Block
[AP86, BS79, Bis87, Bun76, Cal86, CGM85,
CD74, Dem83a, DHS87, ER88, FV62, Geo74,
GLO81, GT81, GU77, Hel76, KB84, Mer85,
Meu84, O’L80a, Ple86, Ris73, RW84a,
RW84b, Saa80, SP87, Sco79a, SHW86, SS87,
Swe77, TG81, Uhl73, Und75, Var72, Wat73].
Block-Oriented [Cal86].
Block-Tridiagonal [Var72]. Boolean
[JH87a, JH87b, JH88]. Both [Mad59].
Bound [PNO85, Var75]. Boundary [FU69].
Bounding [Sco85, Var76]. Bounds
[AK75, Boh75, Bro73, CR79, Des63, FL74,
Hen62, Kåg77a, KPJ82, Lem73, OP64,
Ruh70a, Ste71, Ste73b, Ste77b, Ste79c,
SW80, Var68b, Wed72].
Calculating [BK77, GK65, Ste75c, Ste76a].
Calculation
[BMW67, BS70, CGP76, GW69, KG83,
LS78, MW67, PR69, PW71, Var68a].
Calculations [FF77, Fos86, JMP83, TW72].
Calculus [Dav73]. Can [Bus68, Pan84].
Canonical [Dem83b, Doo79, GW76, MW31,
Par67, TA61, Uhl76, Wil78, Wil79]. Case
[TS87, Wed73a]. CDC [LV75]. CDC-STAR
[LV75]. Certain
[All73, Buc77, HZ68, JO77, Ste73b, Var72].
Chains [Bar87, GM86]. Changes [SS79].
Characteristic [Hou68, Lot56, Sch09].
Characterization [GV74]. Characterizing
[Hoc83]. Chebychev [BP75a, GO88, GV61].
Cholesky
[BBDdH87, GH85, GHL86, HHP88, Hig89,

Golub and Van Loan: gvl.bib

Kie87, Man79, Mei83, ST86, Ste79a].
Choosing [GHW79]. Circle [FV62, Sco85].
Circulant [Cha88]. Class [Eis84, MP74,
Ros69, Ser80, WG78, Wid78, Woz80].
Classes [Bud64]. Cline [BCC78]. Close
[Wil68a]. Closed [Ste71]. Closeness
[Ruh75]. Closest [Pea01, Ruh87]. Clusters
[CD87, Kah67]. Coarse [Bis88b]. Codes
[Hig88d]. Coefficient [Kog55, MdV77].
Coefficients [OP64, Ste77c]. Collection
[DH84]. Collinearity [HV87, Ste87].
Column [Dav86, Fos86, Ste84b].
Combination [Cra86, CM83, War75].
Combinations [Bau65, Mah79].
Comments [Huf88]. Communication
[GR84, Joh87a, SS85a]. Compact [Bun69].
Comparison
[BG76, DR76, GPS76b, GWM76].
Compatibility [OP64]. Complement
[Cot74]. Complete [Kub61]. Complex
[AL73, AL76, BMPW66, BGG88, BG69,
Ebe70, Ebe71, FH60, Fro65, Hig88d, KR80a,
KR80b, MW68b, Mue66, Saa86, Sea69,
Ser80, Var68a, Var68b]. Complexity
[GR84, Mil75]. Computation
[BLL85, Cha85, Cul78, CW79, Doo79, Eld85,
FG86, Giv58, Gol69, GW76, Jen77b, JP71,
Kåg77b, KR80a, KR80b, Mod88, Pai71,
Par74a, Ruh79, Rut69, SP87, War77, WG78,
Wra73, Wra75]. Computational
[FF63, Kan66, KF64, Mil75].
Computations
[BR76, CL88, CW85b, CW85a, DHS87,
FMM77, Gen73b, GL89, Joh87a, Lau81,
Lau85, Luk78, Mol86, OS85, Pai79b, Ple86,
Ric81, Rod82a, Rod82b, Ste73c]. Compute
[GM86, ML78]. Computed
[Don83, DMW83]. Computer
[CMR88, FM67, FMM77, GL81a, KM86b,
LV75, NV75, Pai79a, Sam71]. Computers
[DKH86, DS86, Hoc83, HJ88, KB84, Meu84,
Meu89, OV85, PO87, Sch87]. Computing
[AK75, Bai88a, BS79, Bis88a, BL86, BB71,
BG73, Cha82a, Cha82b, CP77, CVD88,

4

CD74, CWL83, CL86, DK87, FH60, GMS75,
GLO81, GU77, HLPW86, HS86, Hen58,
Hig86a, Hig87a, Hig88b, HVH87, Kåg86,
Loa78a, Loa85a, Luk80, Luk86a, Luk86b,
Pai81, Pai86, PD86, Sch87, Sco84, SB79,
Ste76d, Ste83, Ste85, Var70a, Hig86b].
Concepts [AS83]. Concerning [PT57].
Concurrent [AS83, DSS86, FJL+ 88].
Condensed [DHS87, DR75]. Condition
[AR85, Bro73, Bye84, CP77, CCL82,
CMSW79, CR83, Dem83a, FL74, GL81b,
Hag84, Hig87c, Hig88d, Lem73, Loa87, Loi69,
O’L80b, Ric66b, Saa86, Smi67, Ste80, vdS69,
vdS70, Hig86b]. Conditioned
[Eld77a, Eld84, Eld85, FH72, Gau75b,
GW76, PW79, Ruh70b, Var73, Wil72].
Conditioning [MS73a]. Conditions
[FM84]. Conference [Hea86, KR83].
Configured [JH87b, JH88]. Confluent
[BE73, GP71]. Conjectures [Dem87a].
Conjugate
[Ada85, Ash87, AMS88, Axe80, Cli76b,
CGM85, CGO76, CW77, CW80, JT87, Eis84,
FM84, Gin71, Gre81, Hes80, HS52, JY83,
Jen77a, JMP83, Jor84, Mel87, Meu84, O’L76,
O’L80a, Rei71b, Rei72, RW72b, Sea86,
Ste73a, Ste75a, Woz80, YJ80, vdSdV86].
Connected [BLL85]. Connection [Wed72].
Conquer [Cup81, KM86a]. Considerations
[AGG88, Wra73, Wra75]. Consistency
[vdSV79]. Consistent [BV68, Nic74, You72].
Constrained [BNP88, Bjö84, Eld77b, Eld83,
Hea78, KP81, Loa83, Loa85c, SS79, Dem87c].
Constraint [Gan81]. Constraints
[Eld80, GU70, Mer85]. Construction
[EN83, BPS86a, BPS86b]. Control
[DJK+ 88, DK88, Lau85, Loa82].
Controllability [Pai81]. Convection
[CMdP84]. Convection-Diffusion
[CMdP84]. Converge [Sco79b].
Convergence [AL73, AR85, Bai88a, BP75b,
GO88, Har82, Hen58, HP78, Hua81, Jen77a,
Loi72, PD86, Par65, Par68, Ruh67, Ruh68,
Saa80, Sch64, SS87, Ste75a, Wil65b, Wil68b,

Golub and Van Loan: gvl.bib

You70, vK66, vdSdV86]. Coordinate
[Sch74]. Corresponding [CD74, GLO81].
Cosine [SB79]. Counter [CR83].
Counterexample [Dem87a]. Course
[Ort72, Ort88]. Cray [Bai88b, Cal86,
CDH84, DD88, DE84, DH86, Ker82, Sea86].
Cray-1 [Ker82]. Cray-2
[Bai88b, Cal86, DD88]. Criterion
[Kar74, Lev47]. Cross [Eld85, GHW79].
Cross-Validation [Eld85, GHW79]. Crout
[For60, McK62]. Cryptograms [MM83]. CS
[Loa85a, Pai84]. Cube
[JH87a, JH87b, JH88]. Cyclic
[BP75b, DF76, EHHR88, FH60, Han63,
Hel76, Hen58, Joh84, RW84a, RW84b,
Swe74, Swe77, vK66, HZ68].
D [Enr79]. DAP [MP85]. Data
[AC76, CR79, FG86, GH84, Hoa77, OS85,
SS85a, SS79]. Decomposition
[AG87, AG88, Bai88a, Bis88a, Bre70, BLL85,
Bun82, BKP76, BG69, Cha82a, Cha82b,
Cha84, CM88, CVD88, CMR86, Cup83,
Eld88, Fos86, GR70, GT81, Ham85, HN81,
Hig86a, Hig89, HS88, Kåg85, Kar74, Loa76,
Loa82, Loa85a, Luk80, MPW65, MW65,
Meu89, Nas75, Pai85, Pai86, PD86, PL81,
PS81, Par67, Phi71, Ris73, Ste83, Ste85,
TG81, WAC+ 88, Wed72]. Decompositions
[BS86, BGG88, Gen73a, Gol69, HI83, Pai84,
Ste84a]. Deficient [Wed73a]. Definite
[AR85, BR70, Cra86, CM83, CL86, DI86,
GL81a, GL79, MPW65, MPW66, MW65,
Nic74, PR70, Ste79c, Sun82, Hig89].
Definitions [Rin55, Doo83]. Deflated
[Cha84]. Deflation [Bus71b, Ste81b].
Degeneracy [GKS76, Ste84c]. Degree
[FG65]. Denelcor [DH84]. Dense
[BS86, DGK84, DH86, ISS86, Kau79].
Descent [Cli76a]. Design
[GJMS88, GR84, Lau85, Lev47].
Determination [Ruh69a]. Determined
[DR76, Var70a]. Developing [DS87b].
Diagonal [Bun71a, Var76, Wil68a].

5

Diagonalization [BS79, Ebe71, GH59,
Kog55, MP85, PT57, Sea69, Uhl73].
Diagonalize [Dem83a]. Diagonalizes
[AL73]. Diagonally [FV62, FNP82].
Diagonals [MRK76]. dif [KW87].
Difference [She55, Var72]. Differentiable
[BCS78]. Differential [CGO76, DNT83,
Lan50, Meu89, Nan85, OV85, Var61, Wil78].
Differentiate [GM86]. Differentiation
[GP70, GP73, GP76]. Difficult [Dem88].
Diffusion [CMdP84]. Digital
[KM86b, Opp78]. Dimension [Swe77].
Dimensional [Fro65, Hal58]. Direct
[BCC78, BP71, BD74, BDGG71, BGN70,
CG73, Dor70, Dor73, DER86, Hoc65, JO74,
SS73, Wil61]. Direction
[CJZ83, Hes80, JH87b, Ste73a]. Directions
[JT87]. Discrete
[BR73, BDGG71, Dor70, Dor73, ES86, SS73].
Discretizations [OS81]. Disk [SS73].
Dissection [Geo73]. Distance [Dem87b].
Distributed [Bis88a, Bis88b, EHHR88,
HR88, LC88, Mol86, PJV87].
Distributed-Memory [LC88]. Divide
[Cup81, KM86a]. Divisors [Wil84].
Domain [Meu89]. Dominance [Var76].
Dominant [FV62, FNP82]. Downdating
[BBDdH87, HHP88, Ste79a]. Dubious
[ML78]. Durbin [Cyb80].
E. [Enr79]. Eberlein [Har82]. Eckart
[GHS88]. Economical [Ste76c]. Effect
[Ske81]. Effectiveness [Pai80]. Effects
[LS78, Ste77c, Ste79a]. Efficient
[CVD88, CG73, Eis84, Enr79, Hig86b,
HVH87, Joh87a, LS78, Lau81, MP85, Ruh78,
SL89, Ste80, Sto73, Mel87].
Eigendecompositions [DK87].
Eigenproblem
[AL84, BE68, BNS78, Cup81, Ebe70, MW68c,
Nas75, Pai80, PW70a, Ruh70b, Wil72].
Eigenproblems [Jen72, PR81, Und75].
Eigensolution [JS75]. Eigenspace [CD74].
Eigenstructure [Doo81a]. Eigensystem

Golub and Van Loan: gvl.bib
[GBDM72, SBI+ 70, Var68b, Var70a, WG78].
Eigensystems [GW76, KPJ82].
Eigenvalue
[AGG88, Arn51, BW73, BS70, BS86, BG78,
BL85, BG84b, CJ71, Cra73, Cra76, CW85b,
CW85a, CW86, CL86, DNT83, DHS87,
DKH86, DS87a, Doo81b, ES82, ER80, FH72,
Fri75, Fri77, FNO87, Gol73, Gup72, Jen77a,
JO77, KdV77, Kau74, Kau77, Kub61, KF64,
Lan50, Lew77, LPS87, Loa75a, McC72,
MS73b, Paa71, Par80b, PSS82, PW69,
Rod73, Ruh74, Rut58, Sch86, Sco79a,
SHW86, Smi67, Ste72, Ste73b, Ste74, Ste75b,
Ste76b, Ste78, Ste79c, SW80, War81, Wil65a].
Eigenvalues [BMW67, Bud64, CP77, CJ70,
Cul78, CD74, DMW83, GWDF88, GU77,
Hen58, Kah67, KM86a, Loa84, Loa87,
MW67, Pai71, Pai74b, PNO85, PR69,
Ruh70a, Ruh75, Ruh79, SLN75, Sco84,
Ste76a, Van71, Wil68a, vdS75a].
Eigenvector [BS70, SW80]. Eigenvectors
[Bud64, CP77, CJ70, DK70, DMW83,
GWDF88, Loa87, Pai71, PR69, PW71,
Sco84, Ste69, Ste75c, Var68a].
Eigenwerteinschliessungen [Leh63].
EISPACK [GBDM72, SBI+ 70]. Element
[Geo73]. Elementary
[CdB80, Gou70, Wil84]. Elements [Par76].
Elimination [Bau65, Boh75, Bro73, Bus71a,
Cli73, Coh74, CMR88, Cry68, DK77, DP88,
Geo74, HH89, Ple74, Rei71a, Ske79, Ske80,
Sor85, Str69, TS87]. Elliptic [BPS86a,
BPS86b, CG73, CGO76, She55, Wac66].
Engineers [Jen77b]. Ensemble
[Joh84, Joh85, Joh86, Joh87b, JH88].
Environment [DS87b]. Equality
[BNP88, Eld80, Loa83, Loa85c].
Equality-Constrained [Loa83]. Equation
[BS68, BS72, BD74, BDGG71, Bye83, Bye84,
Cal86, CMdP84, DF76, DH84, Dor70, Dor73,
Erd67, Hoc65, KNP87, KNP88, KW87,
Sto75a, Sto75b, SS73, WZ72]. Equations
[AL84, Axe77, Axe80, Axe85, BG76, BP75a,
Bau65, Bjö87, Bjö88, BP70, BMPW66,

6

Bun85, BP71, BGN70, Cli76a, CG73, CGO76,
Cox81, Cyb80, DNT83, DS83, Doo81b,
DR76, ED83, Joh84, Kog55, Lan70, MP74,
MPW66, MW67, MdV77, Meu89, Nan85,
OP64, OV85, Pai73, Pai74a, PS75, PS78,
PS82a, PS82b, Par80a, PR70, PW79, Rei67,
Rei71b, Rei72, Rob77, RO88, Ros69, Sch09,
She55, Smi70, Ste73a, Ste81b, Sto73, Swa79,
Var61, Var72, Vet75, Wid78, Wil78, dV77].
Equilibration
[Bun71b, McK62, Ske81, vdS69, vdS70].
Equivalence [CW77, Dem83a, Rin55].
Ergodic [Bar87]. Error
[Abd71, ADD88, AL85, Bre70, Cyb78,
Gen73a, Hig87b, JO74, Kie87, Lev47, Mad59,
Mei83, OP64, Pai73, Pai76, PNO85, Pry84,
Pry85, Rob77, Ste71, Ste73b, Ste79a, SW80,
Wil61, Wil68c, Wil71, Woz80, dBP77].
Errors [Boh75, Coc68, HV87, HS66, LS78,
Ste77c, Wil63]. Estimate
[BB71, CMSW79, HZ68, War77, GM86].
Estimates
[Dem87d, Gau75a, Hag84, Kan66, Rob77].
Estimating
[Hig88d, Loa87, O’L80b, PSS82].
Estimation [GL81b, Hig87c, Hig88d, Huf87].
Estimator [Bye84, CCL82]. Estimators
[CR83, GWM76, Ste80, KW87]. ETA
[DD88]. ETA-10P [DD88]. Euclidean
[Blu78]. Evaluate [PS73]. Evaluation
[CJ70, Loa78b]. Even [Joh84]. Exact
[All73]. examples [CR83]. EXCHNG
[Ste76a]. Exclusion [BF60a, BF60b].
Execution [AC84]. Existence
[Cha85, FM84, TW72]. Expansion [Ste84d].
Experiences [CDH84, KL88].
Experiments [PT57, Ric66a]. Explicit
[Dav73, Lan70]. Exploratory [Hoa77].
Exponential
[FL70, Kåg77a, Loa75b, Loa77a, Loa77b,
Loa78a, ML78, War77, Wra73, Wra75].
Extended [DCHH88a, DCHH88b].
Extension [GBDM72]. Extensions
[HL69, LH69]. Extra [Bai88b]. Extremal

Golub and Van Loan: gvl.bib

[AM65]. Extreme [Ste75a].
F.L [Rut69]. FACR [Hoc83]. Factor
[Gre52, Hot57]. Factoring [Ris73, Ser80].
Factorization
[AP86, Bis88b, BBDdH87, BBdH86,
DGKS76, DD88, DSS86, Elm86, ER74,
GH85, GH86, GHL86, GM76, GM86, HS86,
Kie87, Luk86a, Man79, Mei83, Mer85, OS86,
OR88, PJV87, SS79, ST86, Ste77b, Ste79a].
Factorizations
[Cha85, Cha87, CJZ83, GGMS74].
Factorized [Gol76]. Factorizing [Fle76].
Factors [GMS75, HH89]. Far [KP76]. Fast
[CG73, Hig88c, HS88, Hoc65, MP74, Pai79b,
Rat82]. Few [Cul78, Sco84]. Fields [Hen62].
Filter [Lev47]. Find [Blu78, Cra86].
Finding [Bud64, CM83, GWDF88, Van71].
Finite [Geo73, Gre81, Hal58, Tre64, Var72].
Finite-Difference [Var72]. First [Hea86].
Fit [Pea01]. Fitting [Dur60, Mad59].
Floating [Mol67, Ste81a]. Flow
[FG86, OS85]. Form [Aas71, Bus69, Cup83,
Dem83b, Doo79, Giv58, GW76, KR80a,
KR80b, MW68c, MW68d, MW31, Uhl76,
Wat73, Wil78, Wil79, DHS87]. Forms
[DR75, GU70, OR88]. Formulation
[FNO87]. Fortran [Blu78, DCHH88a,
DCHH88b, DE84, DH79, Hig88d, KW87,
LHKK79a, LHKK79b, Ste76a]. Found
[Ruh87]. Fourier [Hoc65]. Frequency
[Lau81]. Fully [DS87a]. Function
[Eld85, Rin55]. Functional [Dav73].
Functions [BCS78, Des63, Fra64a, Fra64b,
Kåg77b, Mir60, Par74a, Par76, PT57].
Funzioni [Bel73].
Game [TW72]. Gauge [Mir60]. Gauss
[BR70, GW69, KP81]. Gauss-Jordan
[BR70]. Gauss-Markov [KP81]. Gaussian
[Boh75, Bro73, Bus71a, Coh74, CMR88,
Cry68, DK77, DP88, HH89, Rei71a, Ske79,
Ske80, Sor85, Str69, TS87]. General
[Bjö84, FJL+ 88, Giv58, Kåg85, KP81,

7

Loa75a, MW68d, McC72, Pai85, Ruh69a,
Swa79, Var68a, Var68b, Var70a].
Generalization
[GHS88, Gou70, Ruh68, You72].
Generalizations [BV68, FV62, Par74b].
Generalized [AL84, BG84b, CGO76, Cra73,
Cra76, JT87, Doo81a, Doo81b, Eld83, Eld85,
ES82, ER80, FH72, FNP82, GHW79, JY83,
JO77, Kåg85, KW87, KdV77, Kau74, Kau77,
Kau87, KF64, Loa73, Loa83, Loa85a, MS73b,
Nas76, Pai79a, Pai79b, Pai85, Pai86, PS81,
PW70a, SS86, Sch66, Ste75b, Ste76b, Ste78,
Ste79c, Ste83, Sun83, Swe74, Van71, War81,
YJ80, dV77, dV82a]. Generalizing
[CCL82, Loa76]. Generate [Uhl76].
Generation [AOU87, Ste80]. Geometric
[PP73]. Geometrical [Nic74]. Geometry
[AM65]. Gershgorin
[FV62, Joh71, Sco85, Ste75b, Var70b].
Gigaflop [DH86]. Given [OP64]. Givens
[Duf74, Gen73a, Gen73b, GH80, Ham74,
MC86, Rat82]. Gleichungen [Jac46].
Global [Har82, HP78, Par68, Wil68b].
GMRES [SS86, Wal88]. Go [KP76]. Good
[GHW79]. Gradient [Ada85, Ash87,
AMS88, Axe80, Cli76b, CGM85, CGO76,
CW77, CW80, Eis84, FM84, Gin71, Gre81,
JY83, Jen77a, JMP83, Jor84, Mel87, Meu84,
O’L76, O’L80a, Rod73, Sea86, Woz80, YJ80].
Gradients [HS52, Rei71b, Rei72, RW72b,
Ste75a, vdSdV86]. Grain [Bis88b]. Gram
[Abd71, Bjö67b, DGKS76, Ric66a, Ruh83,
Saa86]. Gram-Schmidt
[Abd71, Bjö67b, DGKS76, Ric66a, Ruh83].
Grands [GM83]. Granularity [CDH84].
Group [GM86]. Growth [DP88, HH89].
GSV [Pai84]. GSYLV [KW87]. GSYLV[KW87]. Guang [Pai84]. Guide [DBMS78,
GBDM72, Mol80, MLB87, SBI+ 70].
Hamiltonian [Bye83, Bye86, Loa84, PL81].
Hand [OP64, Saa87]. Handbook
[BE68, CL88, AL76]. Hankel [Phi71, Ris73].
having [Cox81]. Havsbad [KR83]. HEP

Golub and Van Loan: gvl.bib

[DH84, LO83]. Hermite [GP71].
Hermitian
[AG87, AG88, BBI71, CM83, DT71, EY39,
Gou70, Hen58, Kah67, Kah75, Mah79,
Mue66, Pai74b, Sch79, Ste69, Ste76d].
Hessenberg [Bus69, Bus71b, GNL79,
Gra86, Ike79, Loa82, MPW70, MW68b,
MW68d, Par67, Par68, Ste76a].
Hessenberg-Schur [GNL79]. Hestenes
[Han88]. Hierarchical [GJM87, GJMS88].
High [Bai88b, DKH86, DS86]. Higher
[Var61]. Higher-Order [Var61].
Householder [BL87, BG67, BG65, CM88,
Cup84, HL69, Kau79, Kau87, LH69, MW68a,
Mue66, PR68, Rei67, SL89, Tsa75, Wal88].
HQR3 [Ste76a]. Hybrid [O’L76].
Hyperbolic [APP88, DI86]. Hypercube
[Bis87, Dav86, Ebe87, FOH87, GH85, GH86,
GWDF88, Hea86, Hea87, HHP88, Joh87a,
KNP87, MvdV87]. Hypercubes
[SS85a, SS85b, WAC+ 88]. Hypermatrix
[NV75].
IBM [DD88, KL88]. ICCG
[Ker82, PO87, dV82b]. Identity [Bre70]. II
[Bjö68, BPS86b, Fra61, Fra64a, GV61,
Hou68, MS78, OR88, Wra75]. III [DK70]. Ill
[Dem87b, DK88, Eld77a, Eld84, Eld85, ES86,
FH72, GW76, OS81, PW79, Ruh70b, Var73,
Wil72]. Ill-Conditioned
[Eld77a, Eld84, Eld85, FH72, GW76, PW79,
Ruh70b, Var73, Wil72]. Ill-Posed
[Dem87b, DK88, ES86, OS81, Var73].
ILLIAC [Luk80]. Impact [GJMS88, GR84].
Implementation
[CVD88, DCHH88a, DSS86, Eis84, KL88,
LO83, Mel87, MP85, Ruh79, Wal88].
Implementations [MvdV87].
Implementing [DGK84, DH86, Tsa75].
Implicit [Dub70, DMW68, Ste81b, Var61].
Implies [JW77, Ske80]. Improved
[BR73, Cha82a, Cha82b]. Improving
[Don83, DMW83]. Inaccurate [CR79].
Inclusion [Kah67]. Incomplete

8

[CJZ83, Elm86, Man79, RW84a, RW84b].
Inconsistent [Axe80]. Incorporating
[Ste70]. Indefinite [AG87, AG88, BG76,
BP71, Fle76, PS75, Saa84]. Independent
[Ste77c]. Inequalities [MM64]. Inertia
[BK77]. Inexact [GO88]. Influence
[Jen77a]. Inner [Win68]. Integral
[JP71, Lan50, Sch09, Smi70]. Integrals
[Loa78a]. Interchanges [Fos86].
Intermediate [SLN75]. Interpretation
[CW80]. Interpreting [Jor87]. Interval
[Yoh79]. Intervals [CW79]. Introduction
[Bel70, Fox64, GK69, Lue73, Mir55, Ste73c,
TA61]. Invariance [Ste84b]. Invariant
[Dem87d, GLR86, MP82, Mir60, Par66,
Ruh70a, Ste71, Ste76d, Var70a]. Inverse
[Asp59, BG78, DGR79, Fri75, Fri77, FNO87,
GK65, PW71, PW79, RW72b, Var68a].
Inverses
[All73, Gau75a, GP73, GP76, Hen62, Ike79,
Nas76, PW70b, Ste77a, Wed73b]. Inversion
[BR70, GM86, Tre64, Tre74, Wat73, Wil61,
Zoh69]. Involving [Hig88c, Loa78a].
Irregular [BD74, BDGG71]. Isolated
[Ste75a]. Iterates [Hen62]. Iteration
[CJ70, CJ71, JO71, JS75, Lan50, Man77,
McK62, Par74b, PW71, PW79, RW72b,
Rut69, Rut70, Ste69, Ste75c, Ste76d, Var68a].
Iterations [Arn51, PP73]. Iterative
[Axe77, Axe85, BI75, BNP88, BS70, Bjö67a,
Bjö68, BB71, BG67, Bun69, DGR79, Eva84,
GO88, GV61, GW66, HY81, JW77, MPW66,
McC72, MdV77, Mol67, NV83, Ple86, Ske80,
Und75, Var62, Wac66, You71, YJ80, EN83].
IV [Fra64b, Luk80].
J [Pai84]. J.-Guang [Pai84]. Jacobi [AL76,
AR85, BS86, Bis87, BG78, BG84a, BE68,
BP75b, Ebe70, Ebe87, FH60, GH84, Han62,
Han63, Hen58, HZ68, Hua75, KG83, Loi72,
MP85, PT57, Ruh67, Ruh68, Rut66, Sam71,
Sch64, SHW86, Sea69, SS87, Ste85, vK66].
Jacobi-Like [Sam71, Ste85]. Jacobi-Type
[AL76, BE68, Ebe70, Hua75]. JNF [KR80a].

Golub and Van Loan: gvl.bib

Jordan [BR70, Dem83b, GW76, KR80a,
KR80b, Loi69].
Kogbetliantz
[Bai88a, CD87, CVD88, PD86]. Kronecker
[Doo79, Kåg86, Wil78, Wil79]. Krylov
[Saa81, Saa84].
Lanczos [CGP76, CD74, CW77, CW79,
CW80, CW85b, CW85a, CWL83, ER80,
Gol74, GLO81, GU77, GUW72, KP74,
KP76, KdV77, Pai70, Pai76, Pai80, Par80a,
PR81, PS79, PSS82, Ruh79, Saa80, Saa82,
Saa87, Sco78, Sco79a, Sco79b, Sim84, Und75,
Wid78, dV82a]. Large
[BPS81, Cul78, CD74, CW79, CW85b,
CW85a, CW86, CWL83, Enr79, ER80,
GL81a, GM76, HH89, Jen72, OS81, Pai71,
PR81, Rei71b, Ruh74, Ruh79, Saa81, Saa82,
Ste74, Ste76b, Und75, Van71, You71].
Large-Scale [BPS81]. Largest
[Cul78, CD74, PSS82]. Latent [GWM76].
Lattice [Cyb84]. LDV [GMS75]. Least
[Abd71, APP88, AK75, BNP88, Bau65,
Bjö67a, Bjö67b, Bjö68, Bjö84, BG67, BG65,
Cli73, Cox81, Cyb84, Eld77a, Eld77b, Eld80,
Eld83, Eld84, Eld85, Gan81, Gen73b, GH80,
Gol65, GKS76, GL80, GP73, GP76, GR70,
GW66, GWM76, HL69, Huf87, Huf88, HV87,
HV88a, HV88b, JO74, Kar74, KP81, LH69,
LH74, Lin61, Loa83, Loa85c, Pai79a, Pai79b,
PS78, PS82a, PS82b, PW70b, Ple74, PR68,
Rei67, Saa86, SS79, Ste77a, Ste87, Wed73a,
vdS75b, Dem87c]. leichtes [Jac46]. Level
[DD88, DCDH88, KL88]. Level-3 [DD88].
Levinson [Cyb80]. Levinson-Durbin
[Cyb80]. Like [Sam71, Ste85, Hig88c].
Limitation [Loa77a]. Linéaires [GM83].
Linear
[Abd71, AM65, ADD88, AC76, Axe77,
Axe80, Axe85, BCC78, BCS78, BG76, BP75a,
BR73, Bau65, Bjö67a, Bjö67b, Bjö68, Bjö84,
BG67, BG73, BMPW66, Buc77, Bun76,
Bun87, BK77, BP71, BG65, Cal86, CDH84,

9

Cli73, CP76, Cox81, Cra86, CM83, Cyb84,
DJK+ 88, DCHH88a, DGK84, DH84, DH86,
DS86, Doo81a, DR76, DS58, Eld80, ES86,
Enr79, FF63, FF77, FM67, Fox64, GJM87,
GJMS88, Geo74, GH80, GK69, Gol65, Gol74,
GL79, GO88, GU70, Hag88, HL69, Hel76,
Hel78, HS52, Hig85, ISS86, JY83, Joh87a,
Kah66, Kan66, Kar74, Kat66, Ker82, Kog55,
KP81, LV75, Lan50, Lan70, Lau85, LH69,
LHKK79a, LHKK79b, Leo80, Lue73, Mah79,
Mak75, MP74, Man77, MG76, MdV77, MP82,
Mir55, NV83, ND77, OP64, Pai74a, Pai79b,
Pai85, PS75, PS78, PS82a, PS82b, Par80a,
PR70, Ple74, PR68, Rei67, Rei71b, Rei72,
Rob77, Ros69, Saa81, Saa84, SS86, SK78,
Sch09, SS79, Ste71, Ste73a, Ste77a, Ste77c,
Ste81b, Sto73, Str88, Var73, Vet75, WAC+ 88,
Wid78, Wil77, Wil78, WR71, You71, dBP77,
vdS70, vdS75b, DCDH88, DCHH88b]. Lines
[Mad59, Pea01]. LINPACK
[CCL82, DBMS78, Bye84]. Linpack-Style
[Bye84]. Local [Cal86].
Local-Memory-Based [Cal86].
Logarithms [Hel68]. Look [Par80a]. Loops
[DH79]. Low [AG87, AG88]. Lower [Var75].
Lowers [Wat88, Dem87c]. Lowest [BS70].
LR [Fra61, MW68b, Wil65b]. LSQR
[PS82a, PS82b]. LU [Cha85, Dav86, DD88,
Elm86, PP73, WAC+ 88]. Lyapunov
[BS68, BN87]. LZ [Kau74].
m [Ada85]. m-step [Ada85]. Machine
[DGK84, Var68b]. Macros [LO83]. Make
[Sco79b]. Manifestations [Cot74]. Markov
[Bar87, GM86, KP81, SS76]. Mathematical
[FMM77, Hoa77, Ric81]. MATLAB
[Mol80, MLB87]. Matrices
[All73, AL76, AOU87, AG87, AG88, AR85,
AC76, Asp59, AP86, Bau63, BR68, BR70,
BBI71, BL87, BBdH86, BG78, BG84a,
BMRW68, Buc74, Bud64, Bun71b, Bun74,
Bun82, BGG88, Bus68, Bus71b, Cra86,
CM83, CD74, CW79, CWL83, Cup84, Cut72,
DT71, Des63, DGK84, DHS87, Dub70,

Golub and Van Loan: gvl.bib

Duf74, DER86, DR75, Ebe65, Ebe71, EY39,
FV62, FL74, FU69, Fle76, Fou84, Fri75,
Fro65, FNP82, Gan59a, Gan59b, Gau75a,
Gau75b, GWDF88, GLR86, GH59, Gou70,
Gra86, GH84, GL81b, Har82, HLPW86,
Hel68, Hen58, Hen62, Hig87c, Hou74, Hua81,
Ike79, JO77, JS75, Joh71, JH87a, Kah67,
Kah75, KP74, KPJ82, Kau87, KG83, LT85,
Lem73, Loi69, Loi72, Lot56, Mah79, MPW70,
MRW70, MW65, MW67, MW68b, MS73a,
Mue66, MW31, Nic74, Osb60, Paa71, Pai71,
Pai74a, Pai74b, PL81, Par66, Par67, Par68,
Par74a, Par74b, Par76, Phi71, PT57, RB68,
Ris73, RW72a, Ruh67, Ruh68, Ruh74, Ruh75,
Ruh79, Rut66, Rut70, Saa86, SLN75, Sch79,
Sea69, Ser80, Ste70, Ste75c, Ste76d, Ste80,
Tre64, Tre74, TA61, Uhl73, Uhl76, Van71,
Var70b, Var79, WAC+ 88, WG78, Wat73,
Wil68a, Wil72, Wil84, vdS69, vdS75a].
Matrix
[Aas71, AK75, AL73, Arn51, Bai88b, Bar87,
BI75, BMW67, BS68, Bel70, BS70, BB71,
BH83, BPS81, BG78, Bre70, BKP76, BR76,
Bus69, BG69, CP77, CS87, CJ70, CMSW79,
CL88, CMR86, Cul78, CL86, Dem83a, DK87,
DSS86, DGR79, Duf77, DS78, ER88, Erd67,
ER74, FH60, Fos86, FOH87, Fra64a, Fra64b,
FG86, GBDM72, GH86, GK82, GPS76a,
GGMS74, GM76, GMS75, Giv58, Gol69,
Gol73, GK65, GL89, GLO81, GNL79, GT81,
GV74, HS86, Hig86c, Hig87a, Hig88b,
Hig88d, Hig88e, Hig89, HS88, Hou58, Hua75,
HVH87, Jen77b, Joh86, JH88, JP71, Kåg77a,
Kåg77b, KR80a, KR80b, KR83, Kau79,
Kau83, Kog55, KM86a, Lan70, Lew77,
Loa75a, Loa75b, Loa77a, Loa77b, Loa78a,
Loa78b, Loa84, Loa85b, Luk78, MRK76,
MM64, MPW65, MW68a, MW68d, MdV77,
Mod88, Mol86, ML78, MS73b, O’L80b,
OS85, OS86, Ort88, Pai73, Pai76, Pan84,
PR69, PR70, Pry85, Ric81, Rin55, Ris73,
Rod73, Ruh69a, Ruh69b, Ruh70b, Ruh78,
Ruh87, Sch68, Sco84, Sco85, SB79, Smi67,
SBI+ 70, Ste69, Ste73c, Ste76a, Ste77b, Ste85,

10

Sun82, TG81, TW72, Var62, Var68a, Var68b,
Var70a, Var75, Vet75, War77, Wat88, Wil61,
WZ72, Wra73, Wra75, Zoh69, Hig86b]. Max
[Bun71b]. Max-Norm [Bun71b].
Maximizing [PT57]. Means [Ruh70a].
Measure [Pry84]. Measurement [Coc68].
Measurements [HN81, Jor87]. Measures
[Ebe65]. Mechanics [BW73]. Memory
[Cal86, EHHR88, GJM87, GJMS88, GHL86,
HR88, JH87a, KNP88, LC88, Mol86, PJV87].
Mesh [BLL85, Geo73]. Method [Abd71,
AL76, AR85, Bar71, BCC78, BMW67, Bis87,
Bjö87, BH83, BG84a, BE68, Bun71a, Cli73,
Cli76a, CGP76, CJ71, CGM85, CGO76,
Cup81, DF76, Ebe70, Ebe87, ER80, FM84,
FH60, Gin71, GHW79, GLO81, GNL79,
GU77, Gup72, Han87, Han88, Har82, HS86,
Hig86c, Hua75, Jen77a, JO71, KW87, Lan50,
Lin61, Loa84, Loa85c, Loi72, Luk86a, MP74,
MdV77, Meu84, MP85, Mue66, Nas75, Pai73,
PJ84, PW79, PT57, PR68, Rei71b, Rod73,
Ruh67, Ruh68, RW72b, Rut66, Rut69,
Rut70, Saa87, Sch74, SS79, Sea69, Ste75a,
Ste83, Und75, Wal88, Wid78, vK66].
Methods [Ada85, Ash87, AMS88, Axe77,
Axe80, Axe85, AP86, BNP88, BW73, BR70,
BV68, BG73, BP75b, Bun76, Bun85, BK77,
BP71, BGN70, Cli76b, CG73, Dem87d,
DS83, DER86, DR76, EN83, Eis84, Eld77b,
Eva84, FF63, FMM77, FNO87, GGMS74,
GMS75, Gol65, Gol76, GO88, GV61, HY81,
Han62, Han63, Hen58, Hes80, HS52, Hot57,
JY83, JH87b, KMN88, Kau83, KF64, Loa83,
McC72, Mel87, Meu89, NV83, O’L80a,
OR88, PO87, Ruh74, Saa80, Saa81, Saa82,
Saa84, SS87, Sim84, Ste73a, Ste75c, Van71,
Var61, Wil61, You70, YJ80, dV82b]. Metric
[Gol76]. MGS [Ple74]. MIMD [CMR88].
Minimal [SS86, Var70b]. Minimization
[BCS78]. Minimized [Arn51]. Minimum
[CL86]. Mirsky [GHS88]. Missized [FG86].
Model [DCHH88a, KP81, Pai85].
Modelling [AC84]. Models
[Dur60, HS66, SS76]. Modern [Wil71].

Golub and Van Loan: gvl.bib

Modes [CGP76]. Modification
[AGG88, BNS78]. Modifications [Ham74].
Modified
[BG84a, EHHR88, Gol73, MW68b, Sea69].
Modifying [GGMS74, GMS75]. Moments
[Hou68]. Monitoring
[Bus71a, ER74, KdV77]. Monitors [LO83].
Most [DE84, DKH86]. MP
[CDH84, DH86, Sea86]. Multicolor [PO87].
Multidimensional [GP70]. Multiple
[JH87b, Wil68a]. Multiplication [Bai88b,
Bre70, CS87, FOH87, MRK76, Pan84].
Multiplications [PS73]. Multiplicative
[Fri75, Pry85]. Multiplying [JH87a].
Multiprocessing [CDH84].
Multiprocessor
[BS86, BL85, Dav86, GH85, GWDF88,
GHL86, KNP87, LC88, LPS87, PJ84, PJV87].
Multiprocessors [EHHR88, Hea86, Hea87,
HR88, Joh87a, JH87b, Mol86].
Multitasking [DH86]. Multivariable
[Lau81]. Multivariate [Ham85, Hot57].
Narrow [Joh85]. Near [Loa85b]. Nearest
[Dem87b, Hig88b]. Nearly
[Cha84, Kah75, Ste81b]. Nearness
[Hig85, Hig88e]. Necessary [FM84, PS73].
Neighboring [Wil84]. Nested [Geo73].
Networks [HI83]. Newer [Hot57]. Newton
[BR68, Hig86c, PW79, RB68]. Nineteen
[ML78]. Non [BS70, Bun69, Ebe65, EY39,
GK69, Hen62, Ste76d]. Non-Hermitian
[EY39, Ste76d]. Non-Iterative [Bun69].
Non-Normal [Hen62]. Non-normality
[Ebe65]. Non-Self-Adjoint [GK69].
Non-Symmetric [BS70]. Nongeneric
[Huf88]. Nonhermitian [Ste85]. Nonlinear
[DS83, GP73, GP76, Lue73]. Nonlinearly
[Hea78]. Nonnormal
[KPJ82, Par74b, vdS75a]. Nonnormality
[Loi69]. Nonscalar [PS73]. Nonseparable
[CG73]. Nonsingular [Uhl76].
Nonsymmetric
[Hou58, Man77, Saa84, SS86, Wid78].

11

Nonsymmetrizable [JY83, YJ80]. Norm
[BP75a, Blu78, BE68, Bun71b, Des63,
Ebe70, Gau75a, Hig88d, Ruh69b].
Norm-Reducing [BE68, Ebe70]. Normal
[CGP76, GH59, Hen62, Hua81, KR80a,
KR80b, Loi72, Ruh67, Ruh75, Ruh87].
normality [Ebe65]. Norms
[BF60a, BF60b, HZ68, Mir60]. Notations
[AS83]. Note [Bai88a, BBI71, BBDdH87,
Buc74, Bun82, Coh74, Dub70, Eld85, GW66,
Ham74, Kie87, Loa78b, Pai84, Rei67, Rei71a,
Ruh78, Ste79b, Sun82, Tsa75, Wil72]. Null
[Fos86, Ste84b]. Number
[Bro73, CMSW79, CR83, Dem83a, GL81b,
Han88, Hig87c, PS73, Saa86, Hig86b].
Numbers [AR85, CP77, FL74, Lem73,
Loi69, O’L80b, Smi67, vdS69]. Numerical
[BG73, Bun87, Bus71a, CdB80, CG73,
CGO76, Cyb80, Cyb84, Dem83b, Dem84,
Dem88, DS83, Eld77b, Enr79, ER80, Fox64,
FNO87, GP70, GR84, Gol65, Gol74, Hag88,
Hea78, Hel78, Hig85, Hou74, IP87, JW77,
Kåg77b, KR80a, KR80b, Kah66, KMN88,
Lau85, Mil75, Ort72, Pai81, Ruh69a, Ruh83,
She55, Ske79, Ske80, Ste74, Var73, War77,
Wil77, dV77]. Numerically
[Bus71b, GH84, Pai79b]. Numérique
[GM83]. numerisch [Jac46].
O. [Enr79]. Oblique [Gre52, Saa82].
Observation [Lin61]. observations
[Cli76b]. Oceans [CGP76]. Odd [Joh84].
Odd-Even [Joh84]. One
[BNS78, Hig88d, McC72, Nas75].
One-Norm [Hig88d]. One-Sided [Nas75].
One-Step [McC72]. Operations
[Dor73, ER88]. Operator [BN87, FL70].
Operators
[DS58, GK69, HZ68, Kat66, Lan50, Ste71].
Optimal
[AC76, BI75, Cha88, MS73a, Str69].
Optimale [Leh63]. Optimally
[Bau63, Bus68, FL74, Gau75b].
Optimization

Golub and Van Loan: gvl.bib

[CW80, DS83, Gol76, Hea78, Hes80].
Optimizing [Hoc83]. Order
[GV61, Ste84d, Var61]. Ordering
[Duf74, MC86, Nic74, Ste76a, You72].
Orderings [BV68]. Ordinary [DNT83].
Oriented [Cal86]. Origin
[Hua81, Ste70, Wil68b]. Orthogonal
[AOU87, BB71, ER88, GM76, Gre52, HI83,
Hig88c, MW31, PJV87, Rat82, Sch66, Ste69,
Ste80, vdSV79]. Orthogonalization
[BI75, Bjö67b, PS79, Ric66a, Ruh83]. Other
[GP76, Saa82, LO83]. Over-Determined
[DR76]. Over-Relaxation
[BV68, GV61, PJ84, You70].
Overdetermined
[BCC78, BCS78, BP75a, Cli76a, Cox81].
Package [Yoh79]. Padé [FL70, Loa77a].
Pair [Uhl76]. Pairs [Sun82]. Pairwise
[Sor85]. Parabolic [Var61]. Parallel
[AP86, BBD+ 87, CM88, CKS78, CMR86,
CMR88, DI86, DH84, DS84, DS87a, DS87b,
Eld88, Eva84, ED83, FF77, FG86, GJM87,
GR84, GH85, GHL86, HR88, Hel78, Hoc83,
HJ88, Jor84, Jor87, KNP87, KNP88, LC88,
Luk78, LO83, MRK76, Meu89, Mod88,
ML82, OS85, OS86, OR88, OV85, Ple86,
Rod82a, Rod82b, RO88, Sam71, SK78,
SHW86, Sto73, Sto75a, Sto75b, Swa79].
Parallelized [PJ84]. Parallelizing [Sea86].
Parameter [GHW79, Huf87]. Part
[DS58, Fra64a, Fra64b]. Partial
[Bun74, CGO76, HV88a, HV88b, JS75,
Meu89, OV85, Ske81, Var61]. Partitioned
[Joh71, Var70b]. Parts [Fra61, GV61]. PC
[MLB87]. PC-Matlab [MLB87]. PDFIND
[Cra86]. Pencil [Doo79, Ruh78, Uhl76].
Pencils [BBI71, Dem83a, DK87, Kåg86,
KR83, TW72]. Pereyra [Hig87b].
Performance [DKH86, DS86, Jor87].
Periodic [BG78, BG84a]. Permutations
[GP74]. Perturbation
[DK70, Eld80, ES82, Kåg77a, Kat66, Pai79a,
Ruh70a, Ste73b, Ste77a, Ste77b, Ste78,

12

Ste79b, Ste79c, Ste84d, Sun83, Wat88,
Wed72, Wed73b, Dem87c]. Perturbations
[AG87, AG88, Sch79, vdS75a]. Perturbed
[Pai74b, Ste84b]. Phenomena [CW80].
Piecewise [BCS78]. Pipeline [DGK84].
Pipelined [HS86]. Pite [KR83]. Pivot
[Coh74, Cry68, Duf74]. Pivoting
[Bun71a, Bun74, Dav86, DK77, For60, HH89,
Ser80, Ske81, Sor85, vdS70]. pivots [Cha85].
Plane [Giv58, Ham74, Saa86, Ste76c].
Planes [Pea01]. Point
[Mol67, PJ84, Ste81a]. Points
[Pea01, Ste75a]. Poisson
[Bun69, BD74, BDGG71, BGN70, DF76,
Dor70, Dor73, Hoc65, Hoc83, SS73]. Polar
[Hig86a, HS88]. Pole [MP82]. Polynomial
[Ash87, FG65, JMP83]. Polynomials
[Hig88c, Loa78b, PS73, Ris73]. Poorly
[Var70a]. Portable
[Blu78, BBD+ 87, DS87b, Yoh79]. Posed
[Dem87b, DK88, ES86, OS81, Var73].
Positive [AR85, Bar87, BR70, Cra86, CM83,
CL86, DI86, GL81a, GL79, Hig88b, MPW65,
MPW66, MW65, Nic74, Ris73, dBP77].
Possessing [Rei72]. Power [PP73].
Practical
[CKS78, ML82, Pai70, Saa84, Wra75].
Precision [Gre81]. Preconditioned
[Ada85, Axe85, Eis84, Mel87, Meu84].
Preconditioner [Cha88]. Preconditioners
[BPS86a, BPS86b, JMP83, Jor84].
Preconditioning [Ash87, CMdP84,
CGM85, Osb60, RW84a, RW84b].
Prediction [Cyb84, Lev47, Mak75, MG76].
Presence [CD87]. Primatives [JH87a].
Principal [EY39, FH60]. Principle [Arn51].
Principles [Lin61]. Priori [Wil68c].
Probabilistic [HS66]. Probabilities
[GM86]. Probability [Dem88]. Problem
[AGG88, AC76, Arn51, BG78, BG84b, CJ71,
Cra73, Cra76, DNT83, Dem87b, Dem88,
DS87a, Doo81a, Eld80, ES82, FH72, GL80,
GNL79, GUW72, Hig88f, Huf87, Huf88,
Kåg85, Kar74, Kau74, Kau77, Kub61, KF64,

Golub and Van Loan: gvl.bib

Lan50, LPS87, Par80b, PW70b, Rod73,
Ruh74, Sch66, Smi67, Ste72, Ste75b, Ste76b,
Ste78, Ste79c, Sun83, War81, Wed73a,
Wil65a, vdS75b]. Problems
[Abd71, BNP88, BW73, Bau65, Bjö67b,
Bjö84, BPS81, BPS86a, BPS86b, BL85,
Cli73, CW86, Cyb84, DK88, Eld77a, Eld83,
Eld84, Eld85, ES86, ER80, FU69, FJL+ 88,
Fri75, Fri77, FNO87, FG86, GH80, Gol65,
Gol73, GKS76, GP73, GP76, Gup72, HL69,
Hig85, Hig88e, HV87, JO71, JO77, KdV77,
Kau83, LH69, LH74, Lew77, Loa85c, MW68c,
McC72, MS73b, OS81, Pai79a, Pai79b, PS78,
PS82a, PR68, Rut58, Sch86, SS79, Sco79a,
Ste73b, Ste74, Ste77a, Var73, Dem87c].
Procedure [BS70, GH59, OS81].
Proceedings [DS78, Hea86, KR83].
Process [Bro73, KP76, Pai70, Sch64, Sco78].
Processes [SS76, Wil63, Wil68c].
Processing [APP88, Cyb78, ML82, Opp78].
Processor
[AC84, GJM87, Jor87, Luk86b, MRK76].
Processors
[AP86, Bis88a, BL86, BBD+ 87, BLL85,
DGR79, FJL+ 88, ISS86, Jor84, LO83].
Procrustes [Hig88f, Sch66]. Product
[Cup83, HLPW86, Win68]. Products
[BL87, Cup84, SL89]. Profile
[GPS76a, GPS76b]. Program
[Blu78, CP77]. Programming
[AS83, Lue73, LO83]. Programs
[BBD+ 87, CW85b, DCHH88a, DS87b].
Progress [PR81]. Projection
[Saa82, vdSV79]. Projections [Ste77a].
Proof [HP78]. Propagation [HS66].
Properties [AM65, FU69, Pai81, Ruh70b,
SS85b, You70, Doo83]. Property
[Rei72, You72]. Proposed [Ste81a]. Pseudo
[GK65, GP73, GP76, PW70b, Ste77a,
Wed73b]. Pseudo-Inverse [GK65].
Pseudo-Inverses
[GP73, GP76, PW70b, Ste77a, Wed73b].
Pseudoinverse [Eld83].

13

Q [CD74]. QL
[BMRW68, Dub70, DMW68, HP78]. QR
[BR68, Bis88b, BBdH86, BMRW68, Bye86,
Cha87, CMR86, DGKS76, DT71, Eld88,
Fra61, Gen73a, GM86, Gra86, HS86, Hua81,
Kar74, Luk86a, MPW70, MRW70, Nan85,
Par65, Par66, Par68, PP73, RB68, Ste70,
Ste77b, Ste84a, Wat82, Wil65b, Wil68b].
Quadratic
[AL73, Bai88a, Gan81, GU70, Loi72, PD86,
Ruh67, Ruh68, Sch64, Wil84, vK66].
Quadrature [GW69]. Quasicyclic
[Han62, Hen58]. Queueing [Kau83].
Quotient [Par74b]. QZ
[Kau77, War75, Wil79].
Random [AOU87, Ste80]. Rank
[AG87, AG88, AGG88, BNS78, Cha87,
Fos86, GKS76, Ste84c, TW70, Wat88,
Wed73a, vdSV79, Dem87c].
Rank-Deficient [Wed73a]. Rank-One
[BNS78]. Rank-Revealing [Cha87]. Rate
[Jen77a, vdSdV86]. Rates [Saa80]. Ratio
[GU70]. Rational [BR68, RB68]. Rayleigh
[Par74b, Van71]. Real
[AR85, BS70, BMPW66, Bud64, CJ70,
Cra86, CD74, CW79, Har82, Hig87a, Hig88d,
JS75, Mah79, MPW70, MW31, Rut66,
Sco85, Ste76a, Uhl73, Uhl76]. Realistic
[SW80]. Reasonable [Yoh79].
Reconfigurable [KB84]. Reconstruction
[GH84]. Rectangle [Dor70]. Rectangular
[BD74, CMR86]. Recurrence [Par76].
Recursive [APP88]. Reducing
[BS79, BE68, Bus69, Cut72, Doo83, Ebe70,
GPS76a, Han88, Kåg86, TW70]. Reduction
[Aas71, Cra73, DF76, DHS87, Duf74, DR75,
GPS76b, Hel76, Joh84, MW68c, MW68d,
RW84a, RW84b, Swe74, Swe77].
Reductions [Rei67]. Refined
[Mei83, PNO85]. Refinement
[Bjö67a, Bjö68, BG67, GW66, JW77,
MPW66, Mol67, Ske80]. Refining [Dem87d].
Reflections [Par71]. Reflectors [SP87].

Golub and Van Loan: gvl.bib

Regions [BD74, BDGG71]. Regression
[GWM76, Ste77c, Ste87]. Regular
[FJL+ 88, Geo73]. Regularization
[Eld77a, Eld77b, Eld84, Han87, OS81].
Regulator [AC76]. Related
[MW68c, O’L80a, Pai81, Wil65b]. Relations
[AR85, Hot57, TW72]. Relative [Pry84].
Relaxation
[BV68, GV61, PJ84, Sch74, You70].
Reliability [Dem84]. Reliable
[Enr79, HVH87]. Reorthogonalization
[DGKS76, Pai70, Sim84]. Representation
[BL87, SL89, SS76]. Research [Duf77].
Residual [KPJ82, SS86, Ske81].
Résolution [GM83]. Response [Lau81].
Restoring [vdSV79]. Restricted [AGG88].
Restructuring [BG84a]. Result [Pai84].
Revealing [Cha87]. Review [Mak75].
RGSVD [Kåg86]. Riccati
[AL84, Bye83, Doo81b]. Richardson
[GO88, GV61]. Ridge [GHW79]. Right
[OP64, Saa87]. Rigorous [Var68b]. Ring
[BL86, ISS86]. RMS [Lev47]. Root
[BH83, GWM76, Hig86c]. Roots
[Gen73b, Hig87a, Hou68, Sch09, TW72].
Rotation [APP88, DK70, Ham74, Luk86a].
Rotations
[DI86, GH80, Giv58, PT57, Rat82, Ste76c].
Rounding [Boh75, Kie87, Ste79a, Wil63].
Roundoff
[Abd71, HS66, LS78, MS78, Woz80].
Routine [Cra86]. Routines
[DH84, GBDM72, KL88, KW87, SBI+ 70].
Row [Bau65, Duf74]. Rowwise [PJ84].
Rules [GW69].
Säculärstörungen [Jac46]. Sample [AC76].
Sample-Data [AC76]. Satisfy [Asp59].
Scale [BPS81, CW86, OS81]. Scaled
[Bau63, Bus68, FL74, Ste84a]. Scaling
[GV74, Ske79, Ste84b]. Scattered [CM88].
Scheduling [OS86]. Scheme
[NV75, Ple86, dV82a]. Schemes [KdV77].
Schmidt

14

[Abd71, Bjö67b, DGKS76, Ric66a, Ruh83].
Schur
[BH83, Cot74, GNL79, KW87, PL81, Ste85].
Scientific [Sch87]. Scientists [Jen77b].
Second [FG65, GV61, Ort72, Ort88, Ste84d].
Second-Degree [FG65]. Second-Order
[GV61]. Sectioning [Jen72]. Selection
[Duf74, HV87]. Selective [PS79]. Self
[GK69]. Semi [EN83, GV61, Hig89].
Semi-definite [Hig89]. Semi-Iterative
[GV61, EN83]. Semidefinite [Hig88b].
Seminormal [Bjö87]. Seminumerical
[Knu81]. Seminumerical-Algorithms
[Knu81]. Sense [BCC78]. Sensitivity
[GM86, Loa77b, Pai84, Ste72, Ste77c].
Separable [GP76]. Separate [GP73].
Separation [Var79]. Sequence [Gup72].
Series [Dur60]. Set
[CR83, DCDH88, DCHH88a, DCHH88b].
Sets [Var70b]. Several
[Cli76b, Cut72, GPS76b, Saa87]. Shapes
[JH87a]. Shared [GHL86, JH87a, KNP88].
Shift [BR68, RB68, War75]. Shifted
[DT71, Man79]. Shifts
[Hua81, Ste70, Wil68b]. Short [Dub70].
Should [KP76]. SIAM [Hea86]. Sided
[Bis87, Nas75]. Sides [OP64, Saa87]. Signal
[APP88, Cyb78, Opp78]. Signals [DJK+ 88].
Similarity [DR75, MW68d, Rat82, Ruh69b].
Simple [SW80]. Simplex [Bar71].
Simplification [JY83]. Simultaneous
[CJ70, CJ71, Cul78, JO71, JS75, Rut69,
Rut70, Ste75c, Ste76d, Uhl73]. Single
[Ker82]. Singular
[AK75, Bai88a, Bar87, BS86, Bis88a, BL85,
BLL85, BGG88, BG69, BN87, Cha82a,
Cha82b, Cha84, CVD88, CWL83, Cup83,
Don83, Doo79, Eld83, GK65, GLO81, GR70,
Ham85, HN81, HVH87, Kåg85, Kåg86,
Kar74, Loa73, Loa76, Loa85a, Luk80,
Luk86b, MM83, Nas75, Pai85, Pai86, PD86,
PS81, Par66, Ruh75, Sch86, Ste79b, Ste81b,
Ste83, Ste84a, Ste84d, Sun83, Var75, Wed72].
Size [Coh74, Cry68, Ske81]. Skew [Buc74,

Golub and Van Loan: gvl.bib

Buc77, Bun82, KdV77, Paa71, WG78].
Skew-Symmetric
[Buc74, Buc77, KdV77, WG78]. Slowly
[Sco79b]. Small [CDH84, Ste84d, Cha85].
Smallest [Bar87, Cul78, HVH87, Var75,
Wat88, Dem87c]. Social [SS76]. Software
[AL84, Dem84, Hoa77, KMN88, MS78,
Ric81, Sco79a, Yoh79]. Solution
[Abd71, Arn51, Axe77, BCS78, BP75a, BS72,
BW73, Bjö67a, Bjö68, Bjö88, BP70, BE68,
BMPW66, BL85, Buc77, BD74, BDGG71,
Cal86, Cli73, Cli76a, CG73, CGO76, Cox81,
DI86, DF76, Dor70, Dor73, DR76, Ebe70,
Enr79, ER80, ED83, FM67, GP70, GH80,
GL81a, GW66, Gup72, HR88, Hig88c, Hoc65,
Huf88, Jen72, Joh84, Ker82, Kog55, Kub61,
KF64, LV75, Lan50, Lan70, MPW66, MW67,
MdV77, ML82, OV85, Pai74a, Pai79a, PS75,
PR70, Rei67, Rei71b, RO88, Ruh78, Rut58,
Sch66, SS79, She55, Sto73, SS73, Und75,
Var72, Var73, Wac66, WAC+ 88, You71].
Solutions
[BG67, BG65, Cha84, CP76, CR79, DK88,
GR70, Hig88a, OP64, Vet75, vdS75b]. Solve
[Kau74]. Solver [Bun69, Hoc83, LC88].
Solvers [CKS78, DKH86, DS84, Joh86,
SK78, Sto75a, Sto75b]. Solving
[ADD88, AL85, BCC78, BG76, Bau65,
Bjö67b, Bun76, Bun85, BK77, BP71,
BGN70, CMdP84, Doo81b, EHHR88, GP71,
Gol65, GO88, HL69, HS52, Hig87b, Joh85,
Joh87b, KNP87, KNP88, KW87, KB84,
Kau77, LH69, LH74, MP74, Pai73, Par80a,
Ros69, Saa81, Saa82, Saa84, Saa87, SS86,
Sch86, Ste73a, Swa79, Swe77, Var61, WZ72].
Some [BS68, Bro73, BK77, Cyb78, DS84,
DSS86, DR76, FL74, FU69, Gol73, Gol74,
Hel76, Kan66, Kau77, Kub61, Loa83, Par74b,
Saa84, Saa86, Wil77, dV82b]. SOR
[Eva84, Nic74, Ruh74]. Space
[Fos86, Pea01]. Spaces [AM65, Hal58].
Sparse [ADD88, Bun76, BR76, Cul78,
CD74, CW79, Duf74, Duf77, DER86, DR75,
DR76, DS78, ER74, ER80, Geo74, GH80,

15

GL81a, GPS76a, GM76, GL81b, HS86,
Kau79, Kau87, Lew77, Luk78, Pai71, PS75,
PS78, PS82a, PS82b, Rei71b, RW72a,
Ruh74, Ruh79, SLN75, Ste76b, Und75].
Special [Ros69, vK66]. Specified
[CW79, PW71]. Spectra [Kah75]. Spectral
[AG87, AG88, Des63, ER80, GH84, Hen62].
Spectrum [CW79, Jen77a, Ste75a]. Speech
[MG76]. Speed
[Bai88b, Hen58, Pan84, PT57]. Sphere
[FG65]. Spread [Sco85]. Square [BH83,
CM88, Eld77b, Gen73b, Hig86c, Hig87a].
Squares [Abd71, APP88, BNP88, Bau65,
Bjö67a, Bjö67b, Bjö68, Bjö84, BG67, BG65,
Cli73, Cox81, Cyb84, Eld77a, Eld80, Eld83,
Eld84, Eld85, Gan81, Gen73b, GH80, Gol65,
GKS76, GL80, GP73, GP76, GR70, GW66,
GWM76, HL69, Huf87, Huf88, HV87,
HV88a, HV88b, JO74, Kar74, KP81, LH69,
LH74, Lin61, Loa83, Loa85c, Pai79a, Pai79b,
PS78, PS82a, PS82b, PW70b, Ple74, PR68,
Rei67, Saa86, SS79, Ste77a, Ste87, Wed73a,
vdS75b, Dem87c]. Squeezing
[DE84, DKH86]. Stability
[Bjö87, Bun85, Bun87, Bus71a, Cyb80,
Cyb84, Dem87a, Elm86, ER74, JW77, Mil75,
Rei71a, Ske79, Ske80, TS87, vdS75b].
Stabilization [Bar71]. Stable
[Bun82, BK77, Bus71b, Cra76, DGKS76,
DK87, GH84, Loa85b, Pai79b, SK78, Var61].
Staircase [Fou84]. Standard
[MW68c, Ste81a]. STAR [LV75, NV75].
STAR-100 [NV75]. State [IP87, JP71].
Stationary [FG65, GM86, GU70].
Statistical [Gol69, Hot57]. Statistics
[Coc68, Ham85]. Step
[McC72, Ada85, NV83]. Stewart [Sun82].
Storage [Mer85, SL89, Ste76c]. Straight
[Mad59]. Strapdown [BI75]. Stratagem
[CM88]. Strategies [Bun74, Cut72].
Strategy [Buz86]. Strong [Bun87].
Structural [BW73, Ple86]. Structure
[Cox81, Gre52, Kåg86, Ruh69a]. Structures
[Vet75]. Study [Loa75b]. Sturm [Gup72].

Golub and Van Loan: gvl.bib

Style [Bye84]. Subject
[AG87, AG88, GU70, Mad59]. Submatrix
[Wat88, Dem87c]. Subprograms
[DCHH88a, LHKK79a, LHKK79b, DCDH88,
DCHH88b]. Subroutines [Ste76a].
Subsequent [SS79]. Subset [HV87].
Subspace [HVH87, Saa81, Saa84].
Subspaces [BS79, BG73, Dem87d, Doo83,
GLR86, Kåg86, Ruh70a, Ste71, Ste73b,
Ste76d, Var70a]. Substitution [Sch09].
Substructuring [BPS86a, BPS86b].
Successive [BV68, GV61, PJ84]. Sufficient
[FM84]. Suitable [AP86]. Sulle [Bel73].
Summability [NV83]. Sun [Pai84].
Supercomputers [Mel87]. Survey
[Axe85, Duf77, Hel78, Hig87c, MM64]. SVD
[BL86, CD87, Han87, HLPW86, Loa83].
Sweeps [Han88]. Sylvester
[KNP87, KNP88, KW87]. Symmetric
[Aas71, AL73, AL76, AGG88, BG76, BMW67,
BR68, BS70, BBI71, BS86, BMRW68, BL85,
Buc74, Buc77, Bud64, Bun71b, Bun74,
Bun82, BG84b, BGG88, BK77, BKP76,
BNS78, BP71, Bus71b, CJ70, Cra73, Cra86,
Cul78, CD74, CW79, CW85b, CW85a,
Cup81, CL86, DK77, DNT83, DI86, DS87a,
Dub70, Ebe71, ER80, Fle76, GUW72, Hig88b,
Hig88f, Jen72, KP74, KdV77, KM86a,
LPS87, Mah79, MPW65, MRW70, MW65,
MW67, MW68a, MW68c, MdV77, Mir60,
Paa71, Pai70, Pai76, Pai80, Par80a, Par80b,
PR70, PR81, PW69, PT57, RB68, Ruh79,
Rut66, Rut70, Saa87, SLN75, Sch68, Sco78,
Sco79a, Sco84, Sco85, Sea69, Ser80, Sim84,
Ste70, Uhl73, Uhl76, Und75, WG78, You70].
Symplectic [Bye83, Loa84]. System
[AL85, BCS78, BP75a, Bis88a, DS84,
Doo81a, Joh86, MPW66, ML82, PR70,
Rei67, SK78, Sto73, dV77]. Systèmes
[GM83]. Systems [ADD88, Axe77, Axe80,
Axe85, BCC78, BG76, Bis88b, BE73, BP70,
Boh75, BMPW66, Buc77, Bun76, Bun85,
BK77, BP71, Cha84, Cha88, CKS78, CS87,
Cli76a, CP76, CR79, Cyb80, DJK+ 88, DI86,

16

DR76, EHHR88, Enr79, ED83, FM67, Fou84,
GJMS88, GP70, GP71, Geo74, GL81a, GL79,
GO88, HR88, Hel76, HS52, Hig87b, Hig88a,
Hig88c, ISS86, JY83, Joh84, Joh85, Joh87b,
JH87b, KB84, Ker82, LV75, MP74, Man77,
MdV77, MP82, ML82, NV83, OR88, PS75,
Par80a, Rei72, Rob77, RO88, Ros69, Ruh78,
Saa81, Saa82, Saa84, Saa87, SS86, Ste73a,
Ste81b, Swe77, Var72, Var73, Wac66,
WAC+ 88, Wid78, You71, dBP77, vdS70].
Systolic [ES86, GK82, HI83, Kun82, Sch86,
ST86, SHW86].
Tales [GP76]. Taxonomy [AMS88].
Tchebychev [Man77]. Techniques
[BCS78, DK77, FJL+ 88, Kan66, KB84].
Test [DCHH88a]. Tests [HS66]. Their
[FU69, RW72a]. Theorem
[FV62, GHS88, Sco85, Sun82]. Theorems
[BF60a, BF60b, ES82, Joh71, Kah67].
Theoretical [AGG88, Wra73]. Theorie
[Jac46]. Theory [BV68, CW85a, DK88,
Doo81a, Eld80, Gan59a, Gan59b, GK69,
Hou74, Kat66, LT85, Lin61, Loa82, MM64,
Nic74, NV83, Ort88, PP73, Ric66b, Sch09,
SP87, Ste75b, Ste78, TW72, TA61, Wed73b].
Thoughts [Kau77]. Three [CR83, Dem87d].
Time [AC84, Dur60, MP82]. Toeplitz
[BBdH86, Bun85, Cha88, Cyb80, CL86,
Ris73, Tre64, Tre74, Wat73, Zoh69].
Topological [SS85b]. Torus [FG86]. Total
[GL80, Huf87, Huf88, HV87, HV88a, HV88b,
Dem87c]. Totally [dBP77]. Tour [Ste76b].
Tracking [PR81]. Transformation
[BR68, BG67, EY39, ER80, Fra61, Kau87,
Nas75, Pry85, Ruh69b, Rut58, Tsa75].
Transformations [AM65, BG65, Dem83a,
DR75, Fro65, Gen73a, Gen73b, Kau79,
MW31, RB68, SL89, Wal88]. Transforming
[Giv58]. Transition [JP71]. Transposition
[JH88]. Trapezoid [Lem73]. Treatment
[Ste74, dV77]. Trees [ER88]. Trench
[Zoh69]. Triangular
[AK75, Bre70, CKS78, Cup84, EHHR88,

Golub and Van Loan: gvl.bib

ER74, ED83, Giv58, HR88, Hig87c, Hig88a,
KNP87, KNP88, Lem73, LC88, Luk86b,
ML82, Par74a, Par76, Phi71, Ris73, RO88].
Triangularization [Fro65, GK82, Hou58].
Triangularizing [Hua75]. Tridiagonal
[Aas71, BMW67, BR68, Bus71b, Dub70,
FU69, Hel76, HP78, Joh84, Joh87b, JH87b,
KB84, Ker82, KM86a, LV75, LPS87, MP74,
RB68, Ros69, Ste70, Sto73, Sto75a, Sto75b,
Swa79, Swe77, Var72, Wil68b, Hig86b].
Tridiagonalization
[CM88, GP74, MW68a, Sch68].
Tridiagonalizing [Pai76]. Tridiagonals
[Mer85, PNO85]. Truncated [Han87].
Truncation [Kar74]. Tutorial [Mak75].
Two [Bis87, Bud64, Cra86, CM83, Fro65,
HLPW86, Uhl73, Var79, Dem87a].
Two-Dimensional [Fro65]. Two-Sided
[Bis87]. Type
[AL76, Axe80, BE68, Ebe70, GP71, Hua75].
Unconstrained [DS83, Gol76]. Undamped
[JO71]. Underdetermined [AL85, CP76].
Underflow [Dem84]. Undersized [Sch86].
Understanding [Wat82]. Unicomputers
[Hoc83]. Uniform [Cli76a]. Uniprocessor
[Cal86]. Unit [FG65]. Unitarily [Mir60].
Unitary
[AM65, Fra61, Fro65, Giv58, Gra86, Hou58].
Unrolling [DH79]. Unstable [Loa85b].
Unsymmetric [Axe80, CJ71, GWDF88,
GL79, JO77, MW67, Saa81, Saa82, You70].
Updating
[Bjö84, Cup84, DGKS76, PNO85, ST86].
Upper [Ste76a]. Usage
[LHKK79a, LHKK79b]. Use
[Cli76b, CG73, DD88, DGR79, GJM87,
Huf87, Pai70, PNO85, Rei72, Saa84]. Used
[RW72b]. User [Mol80]. Users
[DBMS78, MLB87]. Uses [Gol74]. Using
[Bre70, BLL85, CM88, CGP76, DH86,
Ebe87, ER88, Fos86, GWDF88, GH80,
GM86, Hoc65, HV87, JH87a, Loa82, PT57,
SHW86, Sea69, Wal88].

17

Validation [Eld85, GHW79]. Value
[AK75, Bai88a, Bar87, BS86, Bis88a, BL85,
BLL85, BGG88, BG69, Cha82a, Cha82b,
CVD88, Cup83, FU69, GR70, Ham85, HN81,
Kåg85, Loa76, Loa85a, Luk80, MM83, Nas75,
Pai85, Pai86, PD86, PS81, Sch86, Ste83,
Ste84a, Sun83, Var75, Wed72]. Values
[CWL83, Don83, Eld83, FG65, FH60, GK65,
GLO81, GU70, Hen62, HVH87, Loa73,
Lot56, Luk86b, Ruh75, Ste79b, Ste84d].
Vandermonde
[BE73, BP70, GP70, GP71, Gau75a, Gau75b,
GT81, Hig87b, Hig88c, TG81, dV77].
Vandermonde-like [Hig88c]. Variable
[Gol76]. Variables
[GP73, HV87, Mad59, Ste77c]. Variant
[dV82b]. Variation [Hen62]. Vector
[AP86, Bis88a, Blu78, DGK84, DGR79,
Hal58, Jor84, MRK76, Mel87, Meu84, OV85,
PO87, Sch87, Vet75]. Vectorizable [dV82b].
Vectorization [Buz86, Ker82]. Vectors
[BN87, CWL83, GLO81, Pry84, Ruh83,
Ste84b]. Verfahren [Jac46]. Very
[Pai71, Ruh70b, Wil72]. VF [DD88, KL88].
VF/400 [KL88]. Vibration [JO71]. VLSI
[CS87]. Vol [FJL+ 88]. Volume
[CW85b, CW85a]. vorkommenden [Jac46].
W.F [Zoh69]. Ways [ML78]. Weak
[Bun87]. Weighted [Bau65, Eld83].
Weighting [AC76, Loa83, Loa85c]. Weiner
[Lev47]. Which
[Asp59, Bus68, MdV77, Dem87c, Wat88].
Whose [GP73, PR70]. Winograd [Bre70].
Without [Gen73b, Ser80, CP77, Fos86].
WR [Rut58]. WY [BL87, SL89].
X [CDH84, DH86, Sea86]. X-MP [Sea86].
X-MP-2 [CDH84]. X-MP-4 [DH86].
Young [GHS88].

Golub and Van Loan: gvl.bib

18

References

ArbG87
Aas71

[Aas71]

[AG87]

J. O. Aasen. On the reduction of
a symmetric matrix to tridiagonal form. BIT, 11:233–242, 1971.
Abd71

[Abd71]

N. N. Abdelmalek. Roundoff error analysis for Gram-Schmidt
method and solution of linear
least squares problems. BIT, 11: [AG88]
1345–1368, 1971.
ArmC76

[AC76]

E. S. Armstrong and A. K.
Caglayan.
An algorithm for
the weighting matrices in the
sample-data optimal linear regulator problem. Technical Report
TN D-8372, NASA, 1976.

L. Adams and T. Crockett. Modelling algorithm execution time
on processor arrays. IEEE Computer, 17:38–43, 1984.

[AGG88]

L. Adams.
m-step preconditioned conjugate gradient methods. SIAM J. Sci. Statist. Comput., 6:452–463, 1985.

[AK75]

P. Arbenz, W. Gander, and G. H.
Golub. Restricted rank modification of the symmetric eigenvalue
problem: Theoretical considerations. Linear Algebra Appl., 104:
75–95, 1988.

N. Anderson and I. Karasalo. On
computing bounds for the least
singular value of a triangular matrix. BIT, 15:1–4, 1975.
AndL73

[AL73]

AriDD88
[ADD88]

P. Arbenz and G. H. Golub.
On the spectral decomposition of
Hermitian matrices subject to indefinite low rank perturbations
with applications. SIAM J. Matrix Anal. Appl., 9:40–58, 1988.

AndK75

Ada85
[Ada85]

ArbG88

ArbGG88

AdaC84
[AC84]

P. Arbenz and G. H. Golub.
On the spectral decomposition of
Hermitian matrices subject to indefinite low rank perturbations
with applications. Technical Report NA 87-07, Computer Science, Stanford University, Stanford, CA, USA, 1987.

M. Arioli, J. W. Demmel, and
I. S. Duff. Solving sparse linear
systems with sparse backward error. Technical Report CSS 214,
Computer Science and Systems
Division, AERE Harwell, Didcot, [AL76]
UK, 1988.

P. Anderson and G. Loizou. On
the quadratic convergence of an
algorithm that diagonalizes a
complex symmetric matrix. J.
Inst. Math. Appl., 12:261–271,
1973.
AndL76
P. Anderson and G. Loizou. A
Jacobi-type method for complex

Golub and Van Loan: gvl.bib

19

SIAM J. Sci. Statist. Comput., 8:
625–629, 1987.

symmetric matrices (Handbook).
Numer. Math., 25:347–363, 1976.

AxeP86

ArnL84
[AL84]

W. F. Arnold and A. J. Laub. [AP86]
Generalized eigenproblem algorithms and software for algebraic
Riccati equations. Proc. IEEE,
72:1746–1754, 1984.

O. Axelsson and B. Polman. On
approximate factorization methods for block matrices suitable
for vector and parallel processors. Linear Algebra Appl., 77:
3–26, 1986.

AriL85
AlePP88
[AL85]

M. Arioli and A. Laratta. Error
analysis of an algorithm for solv- [APP88]
ing an underdetermined system.
Numer. Math., 46:255–268, 1985.
All73

[All73]

E. L. Allgower. Exact inverses of
certain band matrices. Numer.
Math., 21:279–284, 1973.

AriR85
[AR85]

AmiM65
[AM65]

A. R. Amir-Moez.
Extremal
properties of linear transformations and geometry of unitary
spaces. Mathematics Series 243,
Texas Tech University, Lubbock,
TX, USA, 1965.
[Arn51]
AshMS88

[AMS88]

S. Ashby, T. A. Manteuffel,
and P. E. Saylor.
A taxonomy for conjugate gradient methods. Technical Report UCRL98508, Lawrence Livermore Na- [AS83]
tional Laboratory, Livermore,
CA, USA, 1988.
AndOU87

[AOU87]

S. T. Alexander, C. T. Pan, and
R. J. Plemmons. Analysis of a
recursive least squares hyperbolic
rotation algorithm for signal processing. Linear Algebra Appl., 98:
3–40, 1988.

T. W. Anderson, I. Olkin, and
L. G. Underhill.
Generation [Ash87]
of random orthogonal matrices.

M. Arioli and F. Romani. Relations between condition numbers
and the convergence of the Jacobi
method for real positive definite
matrices. Numer. Math., 46:31–
42, 1985.
Arn51
W. E. Arnoldi. The principle of
minimized iterations in the solution of the matrix eigenvalue
problem. Quart. Appl. Math., 9:
17–29, 1951.
AndS83
G. Andrews and F. B. Schneider.
Concepts and notations for concurrent programming. Comput.
Surveys, 15:1–43, 1983.
Ash87
S. F. Ashby. Polynomial Preconditioning for Conjugate Gra-

Golub and Van Loan: gvl.bib

20

SIAM J. Sci. Statist. Comput., 9:
603–607, 1988.

dient Methods. PhD thesis, Computer Science, University of Illinois, ILL, 1987.
Asp59
[Asp59]

[Bar71]

E. Asplund. Inverse of matrices {aij } which satisfy aij = 0,
j > i + p. Math. Scand., 7:57–60,
1959.
Axe77

[Axe77]

Bar71

Bar87
[Bar87]

O. Axelsson. Solution of linear systems of equations: Iterative methods.
In V. A.
Barker, editor, Sparse Matrix
Techniques: Copenhagen, 1976.
Springer-Verlag, Berlin, Germany, 1977.
[Bau63]
Axe80

[Axe80]

O. Axelsson. Conjugate gradient type methods for unsymmetric and inconsistent systems of [Bau65]
linear equations. Linear Algebra
Appl., 29:1–66, 1980.
Axe85

[Axe85]

O. Axelsson. A survey of preconditioned iterative methods for linear systems of equations. BIT,
25:166–187, 1985.
[BB71]
Bai88a

[Bai88a]

Z. Bai. Note on the quadratic
convergence of Kogbetliantz’s algorithm for computing the singular value decomposition. Linear Algebra Appl., 104:131–140, [BBD+ 87]
1988.
Bai88b

[Bai88b]

D. Bailey. Extra high speed matrix multiplication on the Cray-2.

R. H. Bartels. A stabilization
of the simplex method. Numer.
Math., 16:414–434, 1971.

J. L. Barlow. On the smallest positive singular value of an
M -matrix with applications to
ergodic Markov chains. SIAM
J. Algebraic Discrete Methods, 7:
414–424, 1987.
Bau63
F. L. Bauer. Optimally scaled
matrices. Numer. Math., 5:73–87,
1963.
Bau65
F. L. Bauer. Elimination with
weighted row combinations for
solving linear equations and least
squares problems. Numer. Math.,
7:338–352, 1965. Also in [WR71,
pages 119–133].
BjoB71
Å. Björck and C. Bowie. An iterative algorithm for computing
the best estimate of an orthogonal matrix. SIAM J. Numer.
Anal., 8:358–364, 1971.
BoyBD+87
J. Boyle, R. Butler, T. Disz,
B. Glickfield, E. Lusk, R. Overbeek, J. Patterson, and R. Stevens.
Portable Programs for Parallel
Processors. Holt, Rinehart and
Winston, 1987.

Golub and Van Loan: gvl.bib

21

on irregular regions. SIAM J. Numer. Anal., 11:753–763, 1974.

BojBDdH87

[BBDdH87] A. W. Bojanczyk, R. P. Brent,
P. Van Dooren, and F. R.
BuzDGG71
de Hoog. A note on downdating
the Cholesky factorization. SIAM [BDGG71] B. L. Buzbee, F. W. Dorr, J. A.
George, and G. H. Golub. The diJ. Sci. Statist. Comput., 8:210–
rect solution of the discrete Pois221, 1987.
son equation on irregular regions.
BojBdH86
SIAM J. Numer. Anal., 8:722–
736, 1971.
[BBdH86] A. W. Bojanczyk, R. P. Brent,
and F. R. de Hoog. QR factorization of Toeplitz matrices. Numer.
Math., 49:81–94, 1986.
[BE68]
BerBI71
[BBI71]

A. Berman and A. Ben-Israel. A
note on pencils of Hermitian of
symmetric matrices. SIAM J.
Appl. Math., 21:51–54, 1971.

R. H. Bartels, A. R. Conn, and [BE73]
C. Charalambous. On Cline’s direct method for solving overdetermined linear systems in the
SIAM J. Numer.
L∞ sense.
Anal., 15:255–270, 1978.

Å. Björck and T. Elfving. Algorithms for confluent Vandermonde systems. Numer. Math.,
21:130–137, 1973.

[Bel73]

E. Beltrami. Sulle funzioni bilineari. Giorn. Mat., 11:98–106,
1873.

BarCS78
[BCS78]

J. Boothroyd and P. J. Eberlein. Solution to the eigenproblem by a norm-reducing Jacobitype method (handbook). Numer. Math., 11:1–12, 1968. Also
in [WR71, pages 327–338].
BjoE73

BarCC78
[BCC78]

BooE68

R. H. Bartels, A. R. Conn, and
J. W. Sinclair.
Minimization
techniques for piecewise differentiable functions: The L1 solution
to an overdetermined linear sys- [Bel70]
tem. SIAM J. Numer. Anal., 15:
224–241, 1978.

Bel73

Bel70
R. Bellman. Introduction to Matrix Analysis. McGraw-Hill, New
York, NY, USA, second edition,
1970.

BuzD74
BauF60a
[BD74]

B. L. Buzbee and F. W. Dorr.
The direct solution of the bihar- [BF60a]
monic equation on rectangular
regions and the Poisson equation

F. L. Bauer and C. T. Fike.
Norms and exclusion theorems.
Numer. Math., 2:137–144, 1960.

Golub and Van Loan: gvl.bib

22

lem for periodic Jacobi matrices. In Proceedings Fourth Symposium on Basic Problems of
Numerical Mathematics, Prague,
pages 63–76, 1978.

BauF60b
[BF60b]

F. L. Bauer and C. T. Fike.
Norms and exclusion theorems.
Numer. Math., 2:137–144, 1960.
BusG65

[BG65]

BolG84a

P. A. Businger and G. H. Golub.
[BG84a]
Linear least squares solutions
by Householder transformations.
Numer. Math., 7:269–276, 1965.
Also in [WR71, pages 111–118].

BunG84b

BjoG67
[BG67]

Å. Björck and G. H. Golub. It- [BG84b]
erative refinement of linear least
squares solutions by Householder
transformation. BIT, 7:322–337,
1967.
BusG69

[BG69]

[BGG88]

P. A. Businger and G. H. Golub.
Algorithm 358: Singular value
decomposition of a complex matrix. Comm. ACM, 12:564–565,
1969.

Å. Björck and G. H. Golub. Numerical methods for computing
angles between linear subspaces.
Math. Comp., 27:579–594, 1973.

[BGN70]

BarG76
[BG76]

[BG78]

D. L. Boley and G. H. Golub. The
matrix inverse eigenvalue prob-

BunGG88
A. Bunse-Gerstner and W. B.
Gragg. Singular value decompositions of complex symmetric matrices. J. Comput. Appl. Math.,
21:41–54, 1988.

B. L. Buzbee, G. H. Golub, and
C. W. Nielson. On direct methods for solving Poisson’s equations. SIAM J. Numer. Anal., 7:
627–656, 1970.
BjoH83

V. Barwell and J. A. George.
A comparison of algorithms for [BH83]
solving symmetric indefinite systems of linear equations. ACM
Trans. Math. Software, 2:242–
251, 1976.
BolG78

A. Bunse-Gerstner.
An algorithm for the symmetric generalized eigenvalue problem. Linear
Algebra Appl., 58:43–68, 1984.

BuzGN70

BjoG73
[BG73]

D. Boley and G. H. Golub.
A modified method for restructuring periodic Jacobi matrices.
Math. Comp., 42:143–150, 1984.

[BI75]

Å. Björck and S. Hammarling. A
Schur method for the square root
of a matrix. Linear Algebra Appl.,
52/53:127–140, 1983.
BarI75
I. Y. Bar-Itzhack. Iterative optimal orthogonalization of the
strapdown matrix. IEEE Trans.

Golub and Van Loan: gvl.bib

23

Aerospace Electron. Systems, 11:
30–37, 1975.

Bjo84
[Bjö84]

Bis87
[Bis87]

C. H. Bischof. The two-sided
block Jacobi method on hypercube architectures. In M. T.
Heath, editor, Hypercube Multiprocessors. SIAM Publications,
[Bjö87]
Philadelphia, PA, USA, 1987.
Bis88a

[Bis88a]

C. H. Bischof. Computing the
singular value decomposition on
a distributed system of vector [Bjö88]
processors.
Technical Report
87 869, Computer Science, Cornell University, Ithaca, NY, USA,
1988.

C. H. Bischof. QR Factorization Algorithms for Coarse Grain
Distributed Systems. PhD thesis,
Computer Science, Cornell University, Ithaca, NY, USA, 1988.

Bjo87
Å. Björck. Stability analysis of
the method of seminormal equations.
Linear Algebra Appl.,
88/89:31–48, 1987.
Bjo88
Å. Björck. Solution of Equations
in RN , volume 1 of Least Squares
Methods: Handbook of Numerical
Analysis. North-Holland, 1988.
BunK77

Bis88b
[Bis88b]

Å. Björck. A general updating
algorithm for constrained linear
least squares problems. SIAM J.
Sci. Statist. Comput., 5:394–402,
1984.

[BK77]

J. R. Bunch and K. Kaufman.
Some stable methods for calculating inertia and solving symmetric linear systems.
Math.
Comp., 31:162–179, 1977.
BunKP76

Bjo67a
[BKP76]
[Bjö67a]

Å. Björck. Iterative refinement
of linear least squares solution I.
BIT, 7:257–278, 1967.
Bjo67b

[Bjö67b]

Å. Björck. Solving linear least [BL85]
squares problems by GramSchmidt orthogonalization. BIT,
7:1–21, 1967.
Bjo68

[Bjö68]

Å. Björck. Iterative refinement
of linear least squares solution II. [BL86]
BIT, 8:8–30, 1968.

J. R. Bunch, K. Kaufman, and
B. N. Parlett. Decomposition
of a symmetric matrix. Numer.
Math., 27:95–109, 1976.
BreL85
R. P. Brent and F. T. Luk. The
solution of singular value and
symmetric eigenvalue problems
on multiprocessor arrays. SIAM
J. Sci. Statist. Comput., 6:69–84,
1985.
BisL86
C. H. Bischof and C. Van Loan.
Computing the SVD on a ring of

Golub and Van Loan: gvl.bib

24

array processors. In J. Cullum
and R. Willoughby, editors, Large
Scale Eigenvalue Problems, pages [BMW67]
51–66. North-Holland, 1986.
BisL87
[BL87]

C. H. Bischof and C. Van Loan.
The WY representation for products of Householder matrices.
SIAM J. Sci. Statist. Comput., 8:
s2–s13, 1987.

[BN87]

R. P. Brent, F. T. Luk, and
C. Van Loan. Computation of the
singular value decomposition using mesh connected processors. J.
[BNP88]
VLSI Comput. Syst., 1:242–270,
1985.
Blu78

[Blu78]

W. Barth, R. S. Martin, and J. H.
Wilkinson. Calculation of the
eigenvalues of a symmetric tridiagonal matrix by the method of
bisection. Numer. Math., 9:386–
393, 1967. Also in [WR71, pages
249–256].
ByeN87

BreLL85
[BLL85]

BarMW67

J. M. Blue. A portable Fortran
program to find the Euclidean
norm of a vector. ACM Trans.
Math. Software, 4:15–23, 1978.
[BNS78]
BowMPW66

[BMPW66] H. J. Bowdler, R. S. Martin,
G. Peters, and J. H. Wilkinson.
Solution of real and complex systems of linear equations. Numer.
Math., 8:217–234, 1966. Also in [Boh75]
[WR71, pages 93–110].
BowMRW68
[BMRW68] H. Bowdler, R. S. Martin,
C. Reinsch, and J. H. Wilkinson. The QR and QL algorithms [BP70]
for symmetric matrices. Numer.
Math., 11:293–306, 1968. Also in
[WR71, pages 227–240].

R. Byers and S. G. Nash. On the
singular vectors of the Lyapunov
operator. SIAM J. Algebraic Discrete Methods, 8:59–66, 1987.
BarNP88
J. L. Barlow, N. K. Nichols,
and R. J. Plemmons. Iterative
methods for equality constrained
least squares problems. SIAM J.
Sci. Statist. Comput., 9:892–906,
1988.
BunNS78
J. R. Bunch, C. P. Nielsen, and
D. C. Sorensen. Rank-one modification of the symmetric eigenproblem. Numer. Math., 31:31–
48, 1978.
Boh75
Z. Bohte. Bounds for rounding
errors in the Gaussian elimination for band systems. J. Inst.
Math. Appl., 16:133–142, 1975.
BjoP70
Å. Björck and V. Pereyra. Solution of Vandermonde systems of
equations. Math. Comp., 24:893–
903, 1970.

Golub and Van Loan: gvl.bib

25

BunP71
[BP71]

J. R. Bunch and B. N. Parlett.
Direct methods for solving symmetric indefinite systems of linear equations. SIAM J. Numer.
Anal., 8:639–655, 1971.

BauR68
[BR68]

BarP75a
[BP75a]

BauR70

I. Barrodale and C. Phillips. Al[BR70]
gorithm 495: Solution of an
overdetermined system of linear equations in the Chebychev
norm. ACM Trans. Math. Software, 1:264–270, 1975.
BroP75b

[BP75b]

K. W. Brodlie and M. J. D. Powell. On the convergence of cyclic
Jacobi methods. J. Inst. Math.
Appl., 15:279–287, 1975.

Å. Björck, R. J. Plemmons, and
H. Schneider. Large-Scale Matrix
Problems. North-Holland, New
York, NY, USA, 1981.

[BR73]

[BR76]

J. H. Bramble, J. E. Pasciak, and
A. H. Schatz. The construction of
preconditioners for elliptic problems by substructuring I. Math. [Bre70]
Comp., 47:103–134, 1986.
BraPS86b

[BPS86b]

I. Barrodale and F. D. K.
Roberts. An improved algorithm
for discrete L1 linear approximation. SIAM J. Numer. Anal., 10:
839–848, 1973.
BunR76

BraPS86a
[BPS86a]

F. L. Bauer and C. Reinsch. Inversion of positive definite matrices by the Gauss-Jordan methods. In J. H. Wilkinson and
C. Reinsch, editors, Handbook
for Automatic Computation Vol.
2: Linear Algebra, pages 45–49.
Springer-Verlag, New York, NY,
USA, 1970.
BarR73

BjoPS81
[BPS81]

F. L. Bauer and C. Reinsch. Rational QR transformation with
Newton shift for symmetric tridiagonal matrices. Numer. Math.,
11:264–272, 1968. Also in [WR71,
pages 257–265].

J. H. Bramble, J. E. Pasciak, and
A. H. Schatz. The construction of
preconditioners for elliptic problems by substructuring II. Math. [Bro73]
Comp., 49:1–17, 1986.

J. R. Bunch and D. J. Rose,
editors. Sparse Matrix Computations. Academic Press, New
York, NY, USA, 1976.
Bre70
R. P. Brent. Error analysis of
algorithms for matrix multiplication and triangular decomposition using Winograd’s identity.
Numer. Math., 16:145–156, 1970.
Bro73
C. G. Broyden. Some condition
number bounds for the Gaus-

Golub and Van Loan: gvl.bib

26

Z. Angew. Math. Mech., 54:125–
126, 1974.

sian elimination process. J. Inst.
Math. Appl., 12:273–286, 1973.

Buc77

BarS68
[BS68]

S. Barnett and C. Storey. Some [Buc77]
applications of the Lyapunov matrix equation. J. Inst. Math.
Appl., 4:33–42, 1968.

Bud64

BenS70
[BS70]

C. F. Bender and I. Shavitt. An
iterative procedure for the calculation of the lowest real eigenvalue and eigenvector of a nonsymmetric matrix. J. Comput.
Phys., 6:146–149, 1970.
BarS72

[BS72]

[Bud64]

[Bun69]

O. Buneman. A compact noniterative Poisson solver. Technical Report 294, Institute for
Plasma Research, Stanford University, Stanford, CA, USA,
1969.
Bun71a

[Bun71a]

J. R. Bunch. Analysis of the diagonal pivoting method. SIAM J.
Numer. Anal., 8:656–680, 1971.

R. H. Bartels and G. W. Stewart. Solution of the equation
AX + XB = C. Comm. ACM,
15:820–826, 1972.

C. Bavely and G. W. Stewart. An
algorithm for computing reducing subspaces by block diagonalization. SIAM J. Numer. Anal.,
16:359–367, 1979.

Bun71b
[Bun71b]

BerS86
[BS86]

M. Berry and A. Sameh. Multiprocessor Jacobi algorithms for
dense symmetric eigenvalue and
singular value decompositions. In [Bun74]
Proceedings International Conference on Parallel Processing,
pages 433–440, 1986.
Buc74

[Buc74]

A. Buckley. A note on matrices
A = 1 + H, H skew-symmetric.

C. D. La Budde. Two classes of
algorithms for finding the eigenvalues and eigenvectors of real
symmetric matrices. J. Assoc.
Comput. Mach., 11:53–58, 1964.
Bun69

BavS79
[BS79]

A. Buckley. On the solution
of certain skew-symmetric linear
systems. SIAM J. Numer. Anal.,
14:566–570, 1977.

J. R. Bunch. Equilibration of
symmetric matrices in the maxnorm. J. Assoc. Comput. Mach.,
18:566–572, 1971.
Bun74
J. R. Bunch. Partial pivoting
strategies for symmetric matrices. SIAM J. Numer. Anal., 11:
521–528, 1974.
Bun76

[Bun76]

J. R. Bunch. Block methods
for solving sparse linear systems.

Golub and Van Loan: gvl.bib

27

symmetric tridiagonal matrices.
BIT, 11:262–270, 1971.

In J. R. Bunch and D. J. Rose,
editors, Sparse Matrix Computations. Academic Press, New
York, NY, USA, 1976.
Bun82
[Bun82]

[BV68]

[BW73]

J. R. Bunch. The weak and
strong stability of algorithms in
numerical linear algebra. Linear Algebra Appl., 88/89:49–66,
1987.

P. A. Businger. Matrices which
can be optimally scaled. Numer.
Math., 12:346–348, 1968.

[Bye83]

P. A. Businger. Reducing a matrix to Hessenberg form. Math.
Comp., 23:819–821, 1969.
Bus71a

[Bus71a]

[Bus71b]

P. A. Businger. Numerically stable deflation of Hessenberg and

R. Byers. Hamiltonian and Symplectic Algorithms for the Algebraic Riccati Equation. PhD thesis, Center for Applied Mathematics,
Cornell University,
Ithaca, NY, USA, 1983.
Bye84

[Bye84]

P. A. Businger. Monitoring the
numerical stability of Gaussian
elimination. Numer. Math., 16:
360–361, 1971.
Bus71b

K. J. Bathe and E. L. Wilson.
Solution methods for eigenvalue
problems in structural mechanics. Internat. J. Numer. Methods
Engrg., 6:213–226, 1973.
Bye83

Bus69
[Bus69]

M. J. M. Bernal and J. H. Verner.
On generalizations of the theory
of consistent orderings for successive over-relaxation methods.
Numer. Math., 12:215–222, 1968.
BatW73

Bus68
[Bus68]

B. L. Buzbee. A strategy for vectorization. Parallel Comput., 3:
187–192, 1986.
BerV68

J. R. Bunch. Stability of methods
for solving Toeplitz systems of
equations. SIAM J. Sci. Statist.
Comput., 6:349–364, 1985.
Bun87

[Bun87]

[Buz86]

J. R. Bunch. A note on the stable
decomposition of skew symmetric
matrices. Math. Comp., 158:475–
480, 1982.
Bun85

[Bun85]

Buz86

R. Byers. A Linpack-style condition estimator for the equation AX − XB T = C. IEEE
Trans. Automat. Control, AC-29:
926–928, 1984.
Bye86

[Bye86]

R. Byers. A Hamiltonian QR algorithm. SIAM J. Sci. Statist.
Comput., 7:212–229, 1986.

Golub and Van Loan: gvl.bib

28

Hill, New York, NY, USA, third
edition, 1980.

Cal86
[Cal86]

D. A. Calihan. Block-oriented,
local-memory-based linear equation solution on the Cray-2: [CDH84]
Uniprocessor algorithms. In Proceedings of the 1986 Conference
on Parallel Processing, pages
375–378, 1986.
CliCL82

[CCL82]

A. K. Cline, A. R. Conn, and
C. Van Loan. Generalizing the [CG73]
LINPACK condition estimator.
In J. P. Hennart, editor, Numerical Analysis, Lecture Notes
in Mathematics 909. SpringerVerlag, New York, NY, USA,
1982.
CulD74

[CD74]

[CGM85]
J. Cullum and W. E. Donath. A
block Lanczos algorithm for computing the Q algebraically largest
eigenvalues and a corresponding
eigenspace of large, sparse real
symmetric matrices.
In Proceedings of the 1974 IEEE Con- [CGO76]
ference on Decision and Control, Phoenix, AZ, pages 505–509,
1974.
ChaD87

[CD87]

J. P. Charlier and P. Van Dooren.
On Kogbetliantz’s SVD algorithm in the presence of clusters. Linear Algebra Appl., 95:
135–160, 1987.
CdB80

[CdB80]

S. D. Conte and C. de Boor. Elementary Numerical Analysis: An
Algorithmic Approach. McGraw-

CheDH84
S. Chen, J. Dongarra, and
C. Hsuing. Multiprocessing linear
algebra algorithms on the Cray
X-MP-2: Experiences with small
granularity. J. Parallel and Distrib. Comput., 1:22–31, 1984.
ConG73
P. Concus and G. H. Golub.
Use of fast direct methods for
the efficient numerical solution of
nonseparable elliptic equations.
SIAM J. Numer. Anal., 10:1103–
1120, 1973.
ConGM85
P. Concus, G. H. Golub, and
G. Meurant. Block preconditioning for the conjugate gradient method. SIAM J. Sci. Statist.
Comput., 6:220–252, 1985.
ConGO76
P. Concus, G. H. Golub, and
D. P. O’Leary. A generalized
conjugate gradient method for
the numerical solution of elliptic partial differential equations.
In J. R. Bunch and D. J. Rose,
editors, Sparse Matrix Computations. Academic Press, New
York, NY, USA, 1976.
CliGP76

[CGP76]

A. K. Cline, G. H. Golub, and
G. W. Platzman. Calculation of
normal modes of oceans using a
Lanczos method. In J. R. Bunch
and D. J. Rose, editors, Sparse

Golub and Van Loan: gvl.bib

29

eigenvectors of real symmetric
matrix by simultaneous iteration.
Comput. J., 13:76–80, 1970.

Matrix Computations, pages 409–
426. Academic Press, New York,
NY, USA, 1976.
Cha82a
[Cha82a]

CliJ71

T. F. Chan. Algorithm 581: An [CJ71]
improved algorithm for computing the singular value decomposition. ACM Trans. Math. Software, 8:84–88, 1982.
Cha82b

[Cha82b]

[Cha84]

ChaJZ83

T. F. Chan. An improved algorithm for computing the singu- [CJZ83]
lar value decomposition. ACM
Trans. Math. Software, 8:72–83,
1982.
Cha84
T. F. Chan. Deflated decomposition solutions of nearly singular
systems. SIAM J. Numer. Anal.,
21:738–754, 1984.

[CKS78]

Cha85
[Cha85]

T. F. Chan. Rank-revealing QR
factorizations. Linear Algebra
Appl., 88/89:67–82, 1987.

[CL88]

T. F. Chan. An optimal circulant preconditioner for Toeplitz
systems. SIAM J. Sci. Statist.
Comput., 9:766–771, 1988.
CliJ70

[CJ70]

M. Clint and A. Jennings. The
evaluation of eigenvalues and

CheKS78
S. Chen, D. Kuck, and A. Sameh.
Practical parallel band triangular systems solvers. ACM Trans.
Math. Software, 4:270–277, 1978.

G. Cybenko and C. Van Loan.
Computing the minimum eigenvalue of a symmetric positive definite Toeplitz matrix. SIAM J.
Sci. Statist. Comput., 7:123–131,
1986.
ColL88

Cha88
[Cha88]

T. F. Chan, K. R. Jackson, and
B. Zhu. Alternating direction incomplete factorizations. SIAM J.
Numer. Anal., 20:239–257, 1983.

CybL86

T. F. Chan. On the existence and
computation of LU factorizations [CL86]
with small pivots. Math. Comp.,
42:535–548, 1985.
Cha87

[Cha87]

M. Clint and A. Jennings. A
simultaneous iteration method
for the unsymmetric eigenvalue
problem. J. Inst. Math. Appl., 8:
111–121, 1971.

T. Coleman and C. Van Loan.
Handbook for Matrix Computations.
SIAM Publications,
Philadelphia, PA, USA, 1988.
Cli73

[Cli73]

A. K. Cline.
An elimination
method for the solution of linear
least squares problems. SIAM J.
Numer. Anal., 10:283–289, 1973.

Golub and Van Loan: gvl.bib

30

Cli76a
[Cli76a]

CosMR88

A. K. Cline. A descent method [CMR88]
for the uniform solution to
overdetermined systems of equations. SIAM J. Numer. Anal., 13:
293–309, 1976.

CliMSW79

Cli76b
[Cli76b]

A. K. Cline. Several observations [CMSW79] A. K. Cline, C. B. Moler, G. W.
Stewart, and J. H. Wilkinson. An
on the use of conjugate gradient
estimate for the condition nummethods. report 76-22, ICASE,
ber of a matrix. SIAM J. Numer.
NASA Langley Research Center,
Anal., 16:368–375, 1979.
Hampton, VA, USA, 1976.
Coc68

CraM83
[CM83]

[CM88]

C. R. Crawford and Y. S. Moon. [Coc68]
Finding a positive definite linear combination of two Hermitian
matrices. Linear Algebra Appl.,
51:37–48, 1983.
[Coh74]
ChaM88
H. Y. Chang and M.Salama. A
parallel Householder tridiagonalization stratagem using scattered
square decomposition. Parallel
Comput., 6:297–312, 1988.

[Cot74]

R. C. Chin, T. A. Manteuffel, and J. de Pillis.
ADI [Cox81]
as a preconditioning for solving the convection-diffusion equation. SIAM J. Sci. Statist. Comput., 5:281–299, 1984.
CosMR86

[CMR86]

W. G. Cochrane. Errors of measurement in statistics. Technometrics, 10:637–666, 1968.
Coh74
A. M. Cohen. A note on pivot size
in Gaussian elimination. Linear
Algebra Appl., 8:361–368, 1974.
Cot74

ChiMdP84
[CMdP84]

M. Costnard, M. Marrakchi, and
Y. Robert. Parallel Gaussian
elimination on an MIMD computer. Parallel Comput., 6:275–
296, 1988.

M. Costnard, J. M. Muller, and [CP76]
Y. Robert. Parallel QR decomposition of a rectangular matrix.
Numer. Math., 48:239–250, 1986.

R. W. Cottle. Manifestations of
the Schur complement. Linear
Algebra Appl., 8:189–211, 1974.
Cox81
M. G. Cox. The least squares
solution of overdetermined linear
equations having band or augmented band structure. IMA J.
Numer. Anal., 1:3–22, 1981.
CliP76
R. E. Cline and R. J. Plemmons.
L1 -solutions to underdetermined
linear systems. SIAM Rev., 18:
92–106, 1976.

Golub and Van Loan: gvl.bib

31

ChaP77
[CP77]

Cry68

S. P. Chan and B. N. Parlett. Al- [Cry68]
gorithm 517: A program for computing the condition numbers of
matrix eigenvalues without computing eigenvectors. ACM Trans.
Math. Software, 3:186–203, 1977. [CS87]
CopR79

[CR79]

J. E. Cope and B. W. Rust.
Bounds on solutions of systems
with inaccurate data. SIAM J.
Numer. Anal., 16:950–963, 1979.

[Cul78]

A. K. Cline and R. K. Rew. A set
of counter examples to three condition number estimators. SIAM
J. Sci. Statist. Comput., 4:602–
[Cup81]
611, 1983.
Cra73

[Cra73]

C. R. Crawford.
Reduction
of a band symmetric generalized eigenvalue problem. Comm. [Cup83]
ACM, 16:41–44, 1973.
Cra76

[Cra76]

C. R. Crawford. A stable generalized eigenvalue problem. SIAM J.
Numer. Anal., 13:854–860, 1976.

K. H. Cheng and S. Sahni. VLSI
systems for band matrix multiplication. Parallel Comput., 4:239–
258, 1987.

J. Cullum. The simultaneous
computation of a few of the algebraically largest and smallest
eigenvalues of a large sparse symmetric matrix. BIT, 18:265–275,
1978.
Cup81
J. J. M. Cuppen. A divide and
conquer method for the symmetric eigenproblem. Numer. Math.,
36:177–195, 1981.
Cup83
J. J. M. Cuppen. The singular
value decomposition in product
form. SIAM J. Sci. Statist. Comput., 4:216–222, 1983.
Cup84

[Cup84]

Cra86
[Cra86]

CheS87

Cul78

CliR83
[CR83]

C. W. Cryer. Pivot size in Gaussian elimination. Numer. Math.,
12:335–345, 1968.

C. R. Crawford. Algorithm 646
PDFIND: A routine to find a positive definite linear combination [Cut72]
of two real symmetric matrices.
ACM Trans. Math. Software, 12:
278–282, 1986.

J. J. M. Cuppen. On updating triangular products of Householder matrices. Numer. Math.,
45:403–410, 1984.
Cut72
E. Cuthill.
Several strategies
for reducing the bandwidth of
matrices. In D. J. Rose and
R. A. Willoughby, editors, Sparse

Golub and Van Loan: gvl.bib

32

Birkhaüser, Boston, MA, USA,
1985.

Matrices and Their Applications.
Plenum Press, New York, NY,
USA, 1972.
ChaVD88
[CVD88]

[CW85b]

J. P. Charlier, M. Vanbegin, and
P. Van Dooren.
On efficient
implementation of Kogbetliantz’s
algorithm for computing the singular value decomposition. Numer. Math., 52:279–300, 1988.
CulW77

[CW77]

CulW85a

CulW86
[CW86]

J. Cullum and R. A. Willoughby.
The equivalence of the Lanczos
and the conjugate gradient algorithms. Technical Report RC6903, IBM, Yorktown Heights, [CWL83]
NY, USA, 1977.
CulW79

[CW79]

J. Cullum and R. A. Willoughby.
Lanczos and the computation in
specified intervals of the spectrum of large, sparse real symmetric matrices. In I. S. Duff and [Cyb78]
G. W. Stewart, editors, Sparse
Matrix Proceedings 1978. SIAM
Publications, Philadelphia, PA,
USA, 1979.
CulW80

[CW80]

J. Cullum and R. A. Willoughby. [Cyb80]
The Lanczos phenomena: An interpretation based on conjugate
gradient optimization. Linear Algebra Appl., 29:63–90, 1980.
CulW85b

[CW85a]

J. Cullum and R. A. Willoughby.
Lanczos Algorithms for Large
Symmetric Eigenvalue Computations, Volume 2: Programs.
Birkhaüser, Boston, MA, USA,
1985.

J. Cullum and R. A. Willoughby. [Cyb84]
Lanczos Algorithms for Large
Symmetric Eigenvalue Computations, Volume 1:
Theory.

J. Cullum and R. A. Willoughby,
editors. Large Scale Eigenvalue
Problems. North-Holland, 1986.
CulWL83
J. Cullum, R. A. Willoughby, and
M. Lake. A Lanczos algorithm for
computing singular values and
vectors of large matrices. SIAM
J. Sci. Statist. Comput., 4:197–
215, 1983.
Cyb78
G. Cybenko.
Error Analysis
of Some Signal Processing Algorithms. PhD thesis, Princeton
University, Princeton, NJ, USA,
1978.
Cyb80
G. Cybenko. The numerical stability of the Levinson-Durbin algorithm for Toeplitz systems of
equations. SIAM J. Sci. Statist.
Comput., 1:303–310, 1980.
Cyb84
G. Cybenko. The numerical stability of the lattice algorithm
for least squares linear prediction
problems. BIT, 24:441–455, 1984.

Golub and Van Loan: gvl.bib

33

DonCHH88b

Dav73
[Dav73]

C. Davis. Explicit functional calculus. Linear Algebra Appl., 6:
193–199, 1973.
Dav86

[Dav86]

G. J. Davis. Column LU pivoting on a hypercube multiprocessor. SIAM J. Algebraic Discrete
Methods, 7:538–550, 1986.

[DCHH88b] J. J. Dongarra, J. Du Croz,
S. Hammarling, and R. J. Hanson. An extended set of Fortran Basic Linear Algebra Subprograms. ACM Trans. Math.
Software, 14:1–17, 1988.
DayD88
[DD88]

DonBMS78
[DBMS78]

J. J. Dongarra, J. R. Bunch,
C. B. Moler, and G. W. Stewart.
LINPACK Users Guide.
Philadelphia, PA, USA, 1978.
dBooP77

[dBP77]

M. J. Dayde and I. S. Duff. Use
of level-3 BLAS in LU factorization on the Cray-2, the ETA10P, and the IBM 3090-200/VF.
Technical Report CSS-229, Computer Science and Systems Division, Harwell Laboratory, Oxon
OX11 ORA, UK, 1988.
DonE84

C. de Boor and A. Pinkus. A [DE84]
backward error analysis for totally positive linear systems. Numer. Math., 27:485–490, 1977.
DonCDH88

J. J. Dongarra and S. Eisenstat.
Squeezing the most out of an algorithm in Cray Fortran. ACM
Trans. Math. Software, 10:221–
230, 1984.
Dem83a

[DCDH88]

J. J. Dongarra, J. Du Croz, I. S.
Duff, and S. Hammarling. A set [Dem83a]
of level 3 Basic Linear Algebra
Subprograms. Technical Report
ANL-MCS-TM-88, Argonne National Laboratory, Argonne, ILL,
1988.
DonCHH88a

[Dem83b]

[DCHH88a] J. J. Dongarra, J. Du Croz,
S. Hammarling, and R. J. Hanson. Algorithm 656: An extended
set of Fortran basic linear algebra
subprograms: Model implementation and test programs. ACM
Trans. Math. Software, 14:18–32, [Dem84]
1988.

J. W. Demmel. The condition
number of equivalence transformations that block diagonalize
matrix pencils. SIAM J. Numer.
Anal., 20:599–610, 1983.
Dem83b
J. W. Demmel. A Numerical Analyst’s Jordan Canonical Form.
PhD thesis, Univ. of California
at Berkeley, Berkeley, CA, USA,
1983.
Dem84
J. W. Demmel. Underflow and
the reliability of numerical soft-

Golub and Van Loan: gvl.bib

34

ces. Numer. Math., 5:185–190,
1963.

ware. SIAM J. Sci. Statist. Comput., 5:887–919, 1984.

DiaF76

Dem87a
[Dem87a]

J. W. Demmel. A counterexample for two conjectures about
stability. IEEE Trans. Automat.
Control, AC-32:340–342, 1987.

[DF76]

Dem87b
[Dem87b]

J. W. Demmel. On the distance
to the nearest ill-posed problem. [DGK84]
Numer. Math., 51:251–289, 1987.
Dem87c

[Dem87c]

J. W. Demmel.
The smallest perturbation of a submatrix
which lowers the rank and constrained total least squares problems. SIAM J. Numer. Anal., 24: [DGKS76]
199–206, 1987.
Dem87d

[Dem87d]

J. W. Demmel. Three methods
for refining estimates of invariant
subspaces. Computing, 38:43–57,
1987.
Dem88

[Dem88]

[DGR79]

J. W. Demmel. The probability
that a numerical analysis problem is difficult. Math. Comp., 50:
449–480, 1988.

I. S. Duff, A. M. Erisman, and [DH79]
J. K. Reid. Direct Methods for
Sparse Matrices. Oxford University Press, 1986.
Des63

[Des63]

DonGK84
J. J. Dongarra, F. G. Gustavson,
and A. Karp. Implementing linear algebra algorithms for dense
matrices on a vector pipeline machine. SIAM Rev., 26:91–112,
1984.
DanGKS76
J. Daniel, W. B. Gragg, L. Kaufman, and G. W. Stewart. Reorthogonalization and stable algorithms for updating the GramSchmidt QR factorization. Math.
Comp., 30:772–795, 1976.
DubGR79

DufER86
[DER86]

M. A. Diamond and D. L. V.
Ferreira. On a cyclic reduction
method for the solution of Poisson’s equation. SIAM J. Numer.
Anal., 13:54–70, 1976.

J. Descloux. Bounds for the spec- [DH84]
tral norm of functions of matri-

P. F. Dubois, A. Greenbaum, and
G. H. Rodrigue. Approximating
the inverse of a matrix for use
on iterative algorithms on vector
processors. Computing, 22:257–
268, 1979.
DonH79
J. Dongarra and A. Hinds. Unrolling loops in Fortran. Software Prac. Experience, 9:219–
229, 1979.
DonH84
J. J. Dongarra and R. E. Hiromoto. A collection of parallel

Golub and Van Loan: gvl.bib

35

linear equation routines for the
Denelcor HEP. Parallel Comput.,
1:133–142, 1984.

DaxK77
[DK77]

DonH86
[DH86]

J. Dongarra and T. Hewitt. Implementing dense linear algebra
algorithms using multitasking on
the Cray X-MP-4 (or approach- [DK87]
ing the gigaflop).
SIAM J.
Sci. Statist. Comput., 7:347–350,
1986.
DonHS87

[DHS87]

J. J. Dongarra, S. Hammarling,
and D. C. Sorensen. Block re- [DK88]
duction of matrices to condensed
form for eigenvalue computations. Technical Report ANLMCS-TM 99, Argonne National
Laboratory, Argonne, IL, USA,
1987.
DelI86

[DI86]

[DKH86]

J. M. Delosme and I. C. F. Ipsen.
Parallel solution of symmetric
positive definite systems with hyperbolic rotations. Linear Algebra Appl., 77:75–112, 1986.

B. N. Datta, C. R. Johnson, [DMW68]
M. A. Kaashoek, R. Plemmons,
and E. D. Sontag. Linear Algebra in Signals, Systems, and
Control.
SIAM Publications,
Philadelphia, PA, USA, 1988.
DavK70

[DK70]

C. Davis and W. M. Kahan. The
rotation of eigenvectors by a perturbation III. SIAM J. Numer.
Anal., 7:1–46, 1970.

DemK87
J. W. Demmel and B. Kågström.
Computing stable eigendecompositions of matrix pencils. Linear Algebra Appl., 88/89:139–
186, 1987.
DemK88
J. W. Demmel and B. Kågström.
Accurate solutions of ill-posed
problems in control theory. SIAM
J. Matrix Anal. Appl., pages 126–
145, 1988.
DonKH86
J. J. Dongarra, L. Kaufman, and
S. Hammarling. Squeezing the
most out of eigenvalue solvers
on high performance computers.
Linear Algebra Appl., 77:113–
136, 1986.
DubMW68

DatJK+88
[DJK+ 88]

A. Dax and S. Kaniel. Pivoting
techniques for symmetric Gaussian elimination. Numer. Math.,
28:221–242, 1977.

[DMW83]

A. Dubrulle, R. S. Martin, and
J. H. Wilkinson. The implicit
QL algorithm. Numer. Math., 12:
377–383, 1968. Also in [WR71,
pages 241–248].
DonMW83
J. J. Dongarra, C. B. Moler, and
J. H. Wilkinson. Improving the
accuracy of computed eigenvalues
and eigenvectors. SIAM J. Numer. Anal., 20:23–46, 1983.

Golub and Van Loan: gvl.bib

36

DeiNT83
[DNT83]

P. Deift, T. Nande, and C. Tome. [Dor70]
Ordinary differential equations
and the symmetric eigenvalue
problem. SIAM J. Numer. Anal.,
20:1–22, 1983.
Don83

[Don83]

[Doo81b]

Dor73
F. W. Dorr. The direct solution
of the discrete Poisson equation
in O(n2 ) operations. SIAM Rev.,
15:412–415, 1973.

J. Day and B. Peterson. Growth
in Gaussian elimination. Amer.
Math. Monthly,
95:489–513,
1988.
DufR75

[DR75]

I. S. Duff and J. K. Reid. On
the reduction of sparse matrices
to condensed forms by similarity
transformations. J. Inst. Math.
Appl., 15:217–224, 1975.
DufR76

[DR76]

P. Van Dooren.
A generalized eigenvalue approach for solving Riccati equations. SIAM J.
Sci. Statist. Comput., 2:121–135,
1981.
Doo83

[Doo83]

[DP88]

P. Van Dooren. The generalized
eigenstructure problem in linear
system theory. IEEE Trans. Automat. Control, AC-26:111–128,
1981.
Doo81b

F. W. Dorr. The direct solution
of the discrete Poisson equation
on a rectangle. SIAM Rev., 12:
248–263, 1970.

DayP88

P. Van Dooren. The computation
of Kronecker’s canonical form of
a singular pencil. Linear Algebra
Appl., 27:103–140, 1979.
Doo81a

[Doo81a]

[Dor73]

J. J. Dongarra. Improving the accuracy of computed singular values. SIAM J. Sci. Statist. Comput., 4:712–719, 1983.
Doo79

[Doo79]

Dor70

I. S. Duff and J. K. Reid.
A comparison of some methods for the solution of sparse
over-determined systems of linear
equations. J. Inst. Math. Appl.,
17:267–280, 1976.
DunS58

[DS58]

P. Van Dooren. Reducing subspaces: definitions, properties
and algorithms. In B. Kågström
and A. Ruhe, editors, Matrix
Pencils, pages 58–73. SpringerVerlag, New York, NY, USA, [DS78]
1983.

N. Dunford and J. Schwartz. Linear Operators, Part I. Interscience, New York, NY, USA,
1958.
DufS78
I. S. Duff and G. W. Stewart, editors.
Sparse Matrix

Golub and Van Loan: gvl.bib

37

Proceedings. SIAM Publications,
Philadelphia, PA, USA, 1978.

DekT71
[DT71]

DenS83
[DS83]

J. E. Dennis and R. Schnabel.
Numerical Methods for Unconstrained Optimization and Nonlinear Equations. Prentice-Hall,
Englewood Cliffs, NJ, USA, 1983.

Dub70
[Dub70]

DonS84
[DS84]

J. J. Dongarra and A. H. Sameh.
On some parallel banded system
solvers. Parallel Comput., 1:223–
235, 1984.

[Duf74]

J. J. Dongarra and D. C.
Sorensen. Linear algebra on high
performance computers. Appl. [Duf77]
Math. Comput., 20:57–88, 1986.
DonS87a

[DS87a]

J. J. Dongarra and D. C.
Sorensen. A fully parallel algo- [Dur60]
rithm for the symmetric eigenvalue problem. SIAM J. Sci.
Statist. Comput., 8:s139–s154,
1987.
DonS87b

[DS87b]

[DSS86]

[dV77]

J. J. Dongarra and D. C.
Sorensen. A portable environment for developing parallel programs. Parallel Comput., 5:175–
186, 1987.
DonSS86

A. Dubrulle. A short note on the
implicit QL algorithm for symmetric tridiagonal matrices. Numer. Math., 15:450, 1970.
Duf74

DonS86
[DS86]

T. J. Dekker and J. F. Traub.
The shifted QR algorithm for
Hermitian matrices. Linear Algebra Appl., 4:137–154, 1971.

I. S. Duff. Pivot selection and row
ordering in Givens reduction on
sparse matrices. Computing, 13:
239–248, 1974.
Duf77
I. S. Duff. A survey of sparse
matrix research. Proc. IEEE, 65:
500–535, 1977.
Dur60
J. Durbin. The fitting of time series models. Rev. Inst. Internat.
Statist., 28:233–243, 1960.
dV77
H. Van de Vel. Numerical treatment of a generalized Vandermonde system of equations. Linear Algebra Appl., 17:149–174,
1977.
dV82a

[dV82a]

J. J. Dongarra, A. Sameh, and
D. Sorensen. Implementation of
some concurrent algorithms for
matrix factorization.
Parallel [dV82b]
Comput., 3:25–34, 1986.

H. A. Van der Vorst. A generalized Lanczos scheme. Math.
Comp., 39:559–562, 1982.
dV82b
H. A. Van der Vorst. A vectorizable variant of some ICCG meth-

Golub and Van Loan: gvl.bib

38

J. Sci. Statist. Comput., 9:589–
600, 1988.

ods. SIAM J. Sci. Statist. Comput., 3:350–356, 1982.

Eis84

Ebe65
[Ebe65]

P. J. Eberlein. On measures [Eis84]
of non-normality for matrices.
Amer. Math. Monthly, 72:995–
996, 1965.
Ebe70

[Ebe70]

P. J. Eberlein.
Solution to
the complex eigenproblem by [Eld77a]
a norm-reducing Jacobi-type
method. Numer. Math., 14:232–
245, 1970. Also in [WR71, pages
404–417].
Ebe71

[Ebe71]

[Eld77b]

P. J. Eberlein. On the diagonalization of complex symmetric
matrices. J. Inst. Math. Appl., 7:
377–383, 1971.
Ebe87

S. C. Eisenstat. Efficient implementation of a class of preconditioned conjugate gradient methods. SIAM J. Sci. Statist. Comput., 2:1–4, 1984.
Eld77a
L. Eldèn. Algorithms for the regularization of ill-conditioned least
squares problems. BIT, 17:134–
145, 1977.
Eld77b
L. Eldèn. Numerical Analysis of
Regularization and Constrained
Least Square Methods. PhD thesis, Linkoping Studies in Science
and Technology, Linkoping, Sweden, 1977.
Eld80

[Ebe87]

P. J. Eberlein. On using the
Jacobi method on a hypercube. [Eld80]
In M. T. Heath, editor, Hypercube Multiprocessors. SIAM Publications, Philadelphia, PA, USA,
1987.
EvaD83

[ED83]

D. J. Evans and R. Dunbar. The [Eld83]
parallel solution of triangular systems of equations. IEEE Trans.
Comput., C-32:201–204, 1983.
EisHHR88

[EHHR88]

S.C Eisenstat, M. T. Heath, C. S. [Eld84]
Henkel, and C. H. Romine. Modified cyclic algorithms for solving
triangular systems on distributed
memory multiprocessors. SIAM

L. Eldèn. Perturbation theory
for the least squares problem
with linear equality constraints.
SIAM J. Numer. Anal., 17:338–
350, 1980.
Eld83
L. Eldèn. A weighted pseudoinverse, generalized singular values,
and constrained least squares
problems. BIT, 22:487–502, 1983.
Eld84
L. Eldèn. An algorithm for the
regularization of ill-conditioned,
banded least squares problems.
SIAM J. Sci. Statist. Comput., 5:
237–254, 1984.

Golub and Van Loan: gvl.bib

39

method for the numerical solution of large sparse generalized symmetric eigenvalue problems. Math. Comp., 35:1251–
1268, 1980.

Eld85
[Eld85]

L. Eldèn.
A note on the
computation of the generalized
cross-validation function for illconditioned least squares problems. BIT, 24:467–472, 1985.
Eld88

[Eld88]

ElsR88
[ER88]

L. Eldèn. A parallel QR decomposition algorithm. Technical Report LiTh Mat R 1988-02,
Mathematics, Linkoping University, Sweden, 1988.
Elm86

[Elm86]

H. Elman. A stability analysis
of incomplete LU factorization.
Math. Comp., 47:191–218, 1986.

Erd67
[Erd67]

EieN83
[EN83]

M. Eiermann and W. Niethammer. On the construction of semiiterative methods. SIAM J. Nu- [ES82]
mer. Anal., 20:1153–1160, 1983.
Enr79

[Enr79]

W. Enright. On the efficient
and reliable numerical solution of
large linear systems of O. D. E.’s.
IEEE Trans. Automat. Control,
AC-24:905–908, 1979.

[ES86]

A. M. Erisman and J. K. Reid.
Monitoring the stability of the
triangular factorization of a [Eva84]
sparse matrix. Numer. Math., 22:
183–186, 1974.
EriR80

[ER80]

I. Erdelyi. On the matrix equation Ax = λBx. J. Math. Anal.
Appl., 17:119–132, 1967.
ElsS82
L. Elsner and J. Guang Sun. Perturbation theorems for the generalized eigenvalue problem. Linear
Algebra Appl., 48:341–357, 1982.
EldS86

EriR74
[ER74]

A. Elster and A. P. Reeves. Block
matrix operations using orthogonal trees. In G. Fox, editor, The
Third Conference on Hypercube
Concurrent Computers and Applications, Vol. II, Applications,
pages 1554–1561. ACM Press,
New York, NY, USA, 1988.

T. Ericsson and A. Ruhe. The [EY39]
spectral transformation Lanczos

L. Eldèn and R. Schreiber. An
application of systolic arrays to
linear discrete ill-posed problems.
SIAM J. Sci. Statist. Comput., 7:
892–903, 1986.
Eva84
D. J. Evans. Parallel SOR iterative methods. Parallel Comput.,
1:3–18, 1984.
EckY39
C. Eckart and G. Young. A principal axis transformation for non-

Golub and Van Loan: gvl.bib

40

Hermitian matrices. Bull. Amer.
Math. Soc., 45:118–121, 1939.

FoxJL+88
[FJL+ 88]

FadF63
[FF63]

D. K. Faddeev and V. N. Faddeva. Computational Methods
of Linear Algebra. W. H. Freeman and Co., San Francisco, CA,
USA, 1963.

FaiL70

FadF77
[FL70]
[FF77]

V. N. Fadeeva and D. K. Fadeev.
Parallel calculations in linear algebra.
Kibernetika, 6:28–40,
1977.

G. E. Forsythe and G. H. Golub.
On the stationary values of a
second-degree polynomial on the
unit sphere.
SIAM J. Appl.
Math., 13:1050–1068, 1965.

W. Fair and Y. Luke. Padé approximations to the operator exponential. Numer. Math., 14:
379–382, 1970.
FenL74

ForG65
[FG65]

G. Fox, M. Johnson, G. Lyzenga,
S. Otto, J. Salmon, and
D. Walker. On Concurrent Processors Vol I: General Techniques
and Regular Problems. PrenticeHall, Englewood Cliffs, NJ, USA,
1988.

[FL74]

T. Fenner and G. Loizou. Some
new bounds on the condition
numbers of optimally scaled matrices. J. Assoc. Comput. Mach.,
1:514–524, 1974.
Fle76

FunG86
[FG86]

[Fle76]
R. E. Funderlic and A. Geist.
Torus data flow for parallel computation of missized matrix problems. Linear Algebra Appl., 77:
149–164, 1986.
[FM67]
ForH60

[FH60]

G. E. Forsythe and P. Henrici.
The cyclic Jacobi method for
computing the principal values of
a complex matrix. Trans. Amer. [FM84]
Math. Soc., 94:1–23, 1960.
FixH72

[FH72]

G. Fix and R. Heiberger. An
algorithm for the ill-conditioned
generalized eigenvalue problem.
SIAM J. Numer. Anal., 9:78–88, [FMM77]
1972.

R. Fletcher. Factorizing symmetric indefinite matrices. Linear Algebra Appl., 14:257–272, 1976.
ForM67
G. E. Forsythe and C. B. Moler.
Computer Solution of Linear Algebraic Systems. Prentice-Hall,
Englewood Cliffs, NJ, USA, 1967.
FabM84
V. Faber and T. Manteuffel. Necessary and sufficient conditions
for the existence of a conjugate
gradient method. SIAM J. Numer. Anal., 21:352–362, 1984.
ForMM77
G. E. Forsythe, M. A. Malcolm,
and C. B. Moler.
Computer

Golub and Van Loan: gvl.bib

41

University Press, Oxford, UK,
1964.

Methods for Mathematical Computations. Prentice-Hall, Englewood Cliffs, NJ, USA, 1977.
FriNO87
[FNO87]

[Fox88]

S. Friedland, J. Nocedal, and
M. L. Overton. The formulation
and analysis of numerical methods for inverse eigenvalue problems. SIAM J. Numer. Anal., 24:
634–667, 1987.
FunNP82

[FNP82]

Fox88

Fra61
[Fra61]

R. E. Funderlic, M. Neuman, and
R. J. Plemmons. Generalized diagonally dominant matrices. Numer. Math., 40:57–70, 1982.

G. Fox, S. W. Otto, and A. J.
Hey. Matrix algorithms on a hypercube I: Matrix multiplication.
Parallel Comput., 4:17–31, 1987.
For60

[For60]

[Fos86]

[Fox64]

[Fra64b]

L. Fox. An Introduction to Numerical Linear Algebra. Oxford

J. S. Frame. Matrix functions and
applications, part IV. IEEE Spectrum, 1:123–131, June 1964.
Fri75

[Fri75]

S. Friedland. On inverse multiplicative eigenvalue problems for
matrices. Linear Algebra Appl.,
12:127–138, 1975.
Fri77

[Fri77]

R. Fourer. Staircase matrices and
systems. SIAM Rev., 26:1–71,
1984.
Fox64

J. S. Frame. Matrix functions and
applications, part II. IEEE Spectrum, 1:102–108, April 1964.
Fra64b

L. V. Foster. Rank and null space
calculations using matrix decomposition without column interchanges. Linear Algebra Appl.,
74:47–71, 1986.
Fou84

[Fou84]

[Fra64a]

G. E. Forsythe. Crout with pivoting. Comm. ACM, 3:507–508,
1960.
Fos86

J. G. F. Francis. The QR transformation: A unitary analogue to
the LR transformation, parts I
and II. Comput. J., 4:265–272,
332–345, 1961.
Fra64a

FoxOH87
[FOH87]

G. Fox, editor. Applications, volume 2 of The Third Conference
on Hypercube Concurrent Computers and Applications. ACM
Press, New York, NY, USA,
1988.

S. Friedland. Inverse eigenvalue
problems. Linear Algebra Appl.,
17:15–52, 1977.
Fro65

[Fro65]

C. E. Froberg. On triangularization of complex matrices by twodimensional unitary transformations. BIT, 5:230–234, 1965.

Golub and Van Loan: gvl.bib

42

FisU69
[FU69]

C. Fischer and R. A. Usmani. [GBDM72] B. S. Garbow, J. M. Boyle, J. J.
Dongarra, and C. B. Moler. MaProperties of some tridiagonal
trix Eigensystem Routines: EISmatrices and their application
PACK Guide Extension. New
to boundary value problems.
York, NY, USA, 1972.
SIAM J. Numer. Anal., 6:127–
142, 1969.
Gen73a
FeiV62

[FV62]

GarBDM72

[Gen73a]

D. G. Feingold and R. S. Varga.
Block diagonally dominant matrices and generalizations of the
Gershgorin circle theorem. Pacific J. Math., 12:1241–1250,
[Gen73b]
1962.
Gan59a

[Gan59a]

F. R. Gantmacher. The Theory
of Matrices, volume 1. Chelsea,
New York, NY, USA, 1959.
Gan59b

[Gan59b]

[Gan81]

[Geo73]

[Geo74]

W. Gander. Least squares with
a quadratic constraint. Numer.
Math., 36:291–307, 1981.

W. Gautschi. Norm estimates for
inverses of Vandermonde matrices. Numer. Math., 23:337–347,
1975.

W. Gautschi. Optimally conditioned Vandermonde matrices.
Numer. Math., 24:1–12, 1975.

J. A. George. Nested dissection
of a regular finite element mesh.
SIAM J. Numer. Anal., 10:345–
363, 1973.

J. A. George. On block elimination for sparse linear systems.
SIAM J. Numer. Anal., 11:585–
603, 1974.
GilGMS74

[GGMS74] P. E. Gill, G. H. Golub, W. Murray, and M. A. Saunders. Methods for modifying matrix factorizations. Math. Comp., 28:505–
535, 1974.

Gau75b
[Gau75b]

W. M. Gentleman. Least squares
computations by Givens transformations without square roots.
J. Inst. Math. Appl., 12:329–336,
1973.

Geo74

Gau75a
[Gau75a]

Gen73b

Geo73

F. R. Gantmacher. The Theory
of Matrices, volume 2. Chelsea,
New York, NY, USA, 1959.
Gan81

W. M. Gentleman. Error analysis
of QR decompositions by Givens
transformations. Linear Algebra
Appl., 10:189–197, 1973.

GolH59
[GH59]

H. H. Goldstine and L. P.
Horowitz. A procedure for the diagonalization of normal matrices.

Golub and Van Loan: gvl.bib

43

J. Assoc. Comput. Mach., 6:176–
195, 1959.
GeoH80
[GH80]

J. A. George and M. T. Heath.
Solution of sparse linear least
squares problems using Givens [GHW79]
rotations. Linear Algebra Appl.,
34:69–83, 1980.
GraH84

[GH84]

W. B. Gragg and W. J. Harrod.
The numerically stable
reconstruction of Jacobi matri- [Gin71]
ces from spectral data. Numer.
Math., 44:317–336, 1984.
GeiH85

[GH85]

G. A. Geist and M. T. Heath.
Parallel Cholesky factorization
on a hypercube multiprocessor. Technical Report ORNL
6190, Oak Ridge Laboratory, [Giv58]
Oak Ridge, TN, USA, 1985.
GeiH86

[GH86]

G. A. Geist and M. T. Heath.
Matrix factorization on a hypercube.
In M. T. Heath, editor, Hypercube Multiprocessors, [GJM87]
pages 161–180. SIAM Publications, 1986.
GeoHL86

[GHL86]

J. A. George, M. T. Heath, and
J. Liu. Parallel Cholesky factorization on a shared memory
multiprocessor. Linear Algebra [GJMS88]
Appl., 77:165–187, 1986.
GolHS88

[GHS88]

G. H. Golub, A. Hoffman, and
G. W. Stewart. A generaliza-

tion of the Eckart–Young–Mirsky
approximation theorem.
Linear Algebra Appl., 88/89:317–
328, 1988.
GolHW79
G. H. Golub, M. Heath, and
G. Wahba. Generalized crossvalidation as a method for choosing a good ridge parameter. Technometrics, 21:215–223, 1979.
Gin71
T. Ginsburg. The conjugate gradient method. In J. H. Wilkinson
and C. Reinsch, editors, Handbook for Automatic Computation
Vol. 2: Linear Algebra, pages 57–
69. Springer-Verlag, New York,
NY, USA, 1971.
Giv58
W. Givens.
Computation of
plane unitary rotations transforming a general matrix to triangular form. SIAM J. Appl. Math.,
6:26–50, 1958.
GalJM87
K. Gallivan, W. Jalby, and
U. Meier. The use of BLAS3 in
linear algebra on a parallel processor with a hierarchical memory. SIAM J. Sci. Statist. Comput., 8:1079–1084, 1987.
GalJMS88
K. Gallivan, W. Jalby, U. Meier,
and A. H. Sameh. Impact of
hierarchical memory systems on
linear algebra algorithm design.
Internat. J. Supercomputing Applic., 2:12–48, 1988.

Golub and Van Loan: gvl.bib

44

GolK65
[GK65]

GeoL81a

G. H. Golub and W. Kahan. Cal- [GL81a]
culating the singular values and
pseudo-inverse of a matrix. J.
Soc. Indust. Appl. Math. Ser. B
Numer. Anal., 2:205–224, 1965.

GriL81b

GohK69
[GK69]

I. C. Gohberg and M. G. Krein.
Introduction to the Theory of
Linear Non-Self-Adjoint Operators. American Mathematical Society, Providence, RI, USA, 1969.

J. A. George and J. W. Liu.
Computer Solution of Large
Sparse Positive Definite Systems.
Prentice-Hall, Englewood Cliffs,
NJ, USA, 1981.

[GL81b]

R. G. Grimes and J. G. Lewis.
Condition number estimation
for sparse matrices. SIAM J.
Sci. Statist. Comput., 2:384–388,
1981.
GolL89

GenK82
[GL89]
[GK82]

W. M. Gentleman and H. T.
Kung. Matrix triangularization
by systolic arrays. In SPIE Proceedings, volume 298, pages 19–
26, 1982.
GolKS76

[GKS76]

GolLO81
[GLO81]

G. H. Golub, V. Klema, and
G. W. Stewart. Rank degeneracy
and least squares problems. Technical Report TR-456, Computer
Science, University of Maryland,
College Park, MD, USA, 1976.

G. H. Golub and C. F. Van
Loan. Unsymmetric positive definite linear systems. Linear Algebra Appl., 28:85–98, 1979.

[GLR86]

GolL80
[GL80]

G. H. Golub, F. T. Luk, and
M. Overton. A block Lanczos
method for computing the singular values and corresponding singular vectors of a matrix. ACM
Trans. Math. Software, 7:149–
169, 1981.
GohLR86

GolL79
[GL79]

G. H. Golub and C. F. Van Loan.
Matrix Computations. The Johns
Hopkins University Press, Baltimore, MD, USA, second edition,
1989.

G. H. Golub and C. F. Van Loan. [GM76]
An analysis of the total least
squares problem. SIAM J. Numer. Anal., 17:883–893, 1980.

I. C. Gohberg, P. Lancaster, and
L. Rodman. Invariant Subspaces
of Matrices With Applications.
John Wiley and Sons, New York,
NY, USA, 1986.
GilM76
P. E. Gill and W. Murray. The orthogonal factorization of a large
sparse matrix. In J. R. Bunch
and D. J. Rose, editors, Sparse

Golub and Van Loan: gvl.bib

45

Matrix Computations, pages 177–
200. Academic Press, New York,
NY, USA, 1976.

systems. Numer. Math., 53:571–
594, 1988.
Gol65

GolM83
[GM83]

[Gol65]
G. H. Golub and G. Meurant. Résolution Numérique des
Grands Systèmes Linéaires, volume 49 of Collection de la Direction des Etudes et Recherches de
l’Electricité de France. Eyolles,
[Gol69]
Paris, France, 1983.
GolM86

[GM86]

G. H. Golub and C. D. Meyer.
Using the QR factorization and
group inversion to compute, differentiate, and estimate the sensitivity of stationary probabilities
for Markov chains. SIAM J. Algebraic Discrete Methods, 7:273– [Gol73]
281, 1986.
GilMS75

[GMS75]

P. E. Gill, W. Murray, and M. A.
Saunders. Methods for comput- [Gol74]
ing and modifying the LDV factors of a matrix. Math. Comp.,
29:1051–1077, 1975.
GolNL79

[GNL79]

G. H. Golub, S. Nash, and
C. Van Loan. A HessenbergSchur method for the matrix
problem AX + XB = C. IEEE [Gol76]
Trans. Automat. Control, AC-24:
909–913, 1979.

G. H. Golub. Numerical methods
for solving linear least squares
problems. Numer. Math., 7:206–
216, 1965.
Gol69
G. H. Golub. Matrix decompositions and statistical computation. In R. C. Milton and
J. A. Nelder, editors, Statistical Computation, pages 365–397.
Academic Press, New York, NY,
USA, 1969.
Gol73
G. H. Golub. Some modified matrix eigenvalue problems. SIAM
Rev., 15:318–344, 1973.
Gol74
G. H. Golub.
Some uses of
the Lanczos algorithm in numerical linear algebra. In J. J. H.
Miller, editor, Topics in Numerical Analysis. Academic Press,
New York, NY, USA, 1974.
Gol76
D. Goldfarb. Factorized variable metric methods for unconstrained optimization.
Math.
Comp., 30:796–811, 1976.

GolO88
Gou70
[GO88]

G. H. Golub and M. Overton. The convergence of inexact [Gou70]
Chebychev and Richardson iterative methods for solving linear

A. R. Gourlay. Generalization of
elementary Hermitian matrices.
Comput. J., 13:411–412, 1970.

Golub and Van Loan: gvl.bib

46

SIAM J. Numer. Anal., 13:236–
250, 1976.

GalP70
[GP70]

G. Galimberti and V. Pereyra.
Numerical differentiation and
the solution of multidimensional [GPS76b]
Vandermonde systems.
Math.
Comp., 24:357–364, 1970.
GalP71

[GP71]

G. Galimberti and V. Pereyra.
Solving confluent Vandermonde
systems of Hermite type. Numer.
Math., 18:44–60, 1971.
[GR70]
GolP73

[GP73]

G. H. Golub and V. Pereyra. The
differentiation of pseudo-inverses
and nonlinear least squares problems whose variables separate.
SIAM J. Numer. Anal., 10:413–
432, 1973.

[GR84]

N. E. Gibbs and W. G. Poole,
Jr. Tridiagonalization by permutations. Comm. ACM, 17:20–24,
1974.
GolP76

[GP76]

GolR70
G. H. Golub and C. Reinsch.
Singular value decomposition and
least squares solutions. Numer.
Math., 14:403–420, 1970. Also in
[WR71, pages 134–151].

D. Gannon and J. Van Rosendale.
On the impact of communication complexity on the design
of parallel numerical algorithms.
IEEE Trans. Comput., C-33:
1180–1194, 1984.
Gra86

[Gra86]

G. H. Golub and V. Pereyra. Differentiation of pseudo-inverses,
separable nonlinear least squares
problems and other tales. In
M. Z. Nashed, editor, Generalized [Gre52]
Inverses and Applications, pages
303–324. Academic Press, New
York, NY, USA, 1976.
GibPS76a

[GPS76a]

N. E. Gibbs, W. G. Poole, and
P. K. Stockmeyer. A comparison of several bandwidth and profile reduction algorithms. ACM
Trans. Math. Software, 2:322–
330, 1976.

GanR84

GibWP74
[GP74]

GibPS76b

N. E. Gibbs, W. G. Poole, and [Gre81]
P. K. Stockmeyer.
An algorithm for reducing the bandwidth
and profile of a sparse matrix.

W. B. Gragg. The QR algorithm
for unitary Hessenberg matrices.
J. Comput. Appl. Math., 16:1–8,
1986.
Gre52
B. Green. The orthogonal approximation of an oblique structure in factor analysis.
Psychometrika, 17:429–440, 1952.
Gre81
A. Greenbaum.
Behavior of
the conjugate gradient algorithm
in finite precision arithmetic.
Technical Report UCRL 85752,

Golub and Van Loan: gvl.bib

47

Lawrence Livermore Laboratory,
Livermore, CA, USA, 1981.
GolT81
[GT81]

G. H. Golub and W. P. Tang. The
block decomposition of a Vandermonde matrix and its applications. BIT, 21:505–517, 1981.
[GV74]
GolU70

[GU70]

G. H. Golub and R. Underwood.
Stationary values of the ratio of
quadratic forms subject to linear constraints. Z. Angew. Math.
[GW66]
Phys., 21:318–326, 1970.
GolU77

[GU77]

G. H. Golub and R. Underwood. The block Lanczos method
for computing eigenvalues. In
J. Rice, editor, Mathematical [GW69]
Software III, pages 364–377. Academic Press, New York, NY,
USA, 1977.
Gup72

[Gup72]

[GUW72]

[GV61]

K. K. Gupta. Solution of eigen- [GW76]
value problems by Sturm sequence method. Internat. J. Numer. Methods Engrg., 4:379–404,
1972.
GolUW72

ods, successive over-relaxation iterative methods, and secondorder Richardson iterative methods, parts I and II. Numer.
Math., 3:147–156, 157–168, 1961.
GolV74
G. H. Golub and J. M. Varah. On
a characterization of the best L2 scaling of a matrix. SIAM J. Numer. Anal., 11:472–479, 1974.
GolW66
G. H. Golub and J. H. Wilkinson.
Note on the iterative refinement
of least squares solution. Numer.
Math., 9:139–148, 1966.
GolW69
G. H. Golub and J. H. Welsch.
Calculation of Gauss quadrature
rules. Math. Comp., 23:221–230,
1969.
GolW76
G. H. Golub and J. H. Wilkinson. Ill-conditioned eigensystems
and the computation of the Jordan canonical form. SIAM Rev.,
18:578–619, 1976.
GeiWDF88

G. H. Golub, R. Underwood, and [GWDF88] G. A. Geist, R. C. Ward, G. J.
J. H. Wilkinson. The Lanczos alDavis, and R. E. Funderlic.
gorithm for the symmetric Ax =
Finding eigenvalues and eigenλBx problem. Technical Report
vectors of unsymmetric matrices
STAN-CS-72-270, Computer Sciusing a hypercube multiprocesence, Stanford University, Stansor.
In G. Fox, editor, The
ford, CA, USA, 1972.
Third Conference on Hypercube
Concurrent Computers and ApGolV61
plications, Vol. II, Applications,
G. H. Golub and R. S. Varga.
pages 1577–1582. ACM Press,
Chebychev semi-iterative methNew York, NY, USA, 1988.

Golub and Van Loan: gvl.bib

48

GunWM76
[GWM76]

R. F. Gunst, J. T. Webster, and
R. L. Mason. A comparison of
least squares and latent root regression estimators. Technometrics, 18:75–83, 1976.
Hag84

[Hag84]

Han87
[Han87]

Han88
[Han88]

W. Hager. Condition estimates.
SIAM J. Sci. Statist. Comput., 5:
311–316, 1984.
Hag88

[Hag88]

W. Hager. Applied Numerical
Linear Algebra. Prentice-Hall,
Englewood Cliffs, NJ, USA, 1988.
Hal58

[Hal58]

[Har82]

P. Halmos. Finite Dimensional
Vector Spaces. Van Nostrand,
New York, NY, USA, 1958.

S. Hammarling. A note on modifications to the Givens plane rotation. J. Inst. Math. Appl., 13:
215–218, 1974.

[Hea78]

S. J. Hammarling. The singular value decomposition in multivariate statistics. ACM SIGNUM [Hea86]
Newslett., 20:2–25, 1985.
Han62

[Han62]

E. R. Hansen. On quasicyclic Jacobi methods. J. Assoc. Comput.
Mach., 9:118–135, 1962.
Han63

[Han63]

E. R. Hanson. On cyclic Jacobi
methods. SIAM J. Appl. Math.,
11:448–459, 1963.

V. Hari. On the global convergence of the Eberlein method for
real matrices. Numer. Math., 39:
361–370, 1982.
Hea78

Ham85
[Ham85]

P. C. Hansen.
Reducing the
number of sweeps in Hestenes
method. In E. F. Deprettere,
editor, Singular Value Decomposition and Signal Processing.
North-Holland, 1988.
Har82

Ham74
[Ham74]

P. C. Hansen. The truncated
SVD as a method for regularization. BIT, 27:534–553, 1987.

M. T. Heath. Numerical Algorithms for Nonlinearly Constrained Optimization. PhD thesis, Computer Science, Stanford
University, Stanford, CA, USA,
1978.
Hea86
M. T. Heath, editor. Proceedings
of First SIAM Conference on Hypercube Multiprocessors. SIAM
Publications, Philadelphia, PA,
USA, 1986.
Hea87

[Hea87]

M. T. Heath, editor. Hypercube Multiprocessors. SIAM Publications, Philadelphia, PA, USA,
1987.

Golub and Van Loan: gvl.bib

49

elimination with pivoting. SIAM
J. Matrix Anal. Appl., 10:155–
164, 1989.

Hel68
[Hel68]

B. W. Helton. Logarithms of matrices. Proc. Amer. Math. Soc.,
19:733–736, 1968.
Hel76

[Hel76]

HenHP88
[HHP88]

D. Heller.
Some aspects of
the cyclic reduction algorithm for
block tridiagonal linear systems.
SIAM J. Numer. Anal., 13:484–
496, 1976.
Hel78

[Hel78]

D. Heller. A survey of parallel
algorithms in numerical linear algebra. SIAM Rev., 20:740–777,
1978.

HelI83
[HI83]

Hen58
[Hen58]

P. Henrici. On the speed of
convergence of cyclic and quasicyclic Jacobi methods for computing the eigenvalues of Hermitian matrices. SIAM J. Appl.
Math., 6:144–162, 1958.

[Hig85]

P. Henrici. Bounds for iterates,
inverses, spectral variation, and
fields of values of non-normal matrices. Numer. Math., 4:24–40,
[Hig86a]
1962.
Hes80

[Hes80]

M. R. Hestenes.
Conjugate
Direction Methods in Optimization.
Springer-Verlag, Berlin,
Germany, 1980.
[Hig86b]
HigH89

[HH89]

N. J. Higham and D. J. Higham.
Large growth factors in Gaussian

D. E. Heller and I. C. F. Ipsen.
Systolic networks for orthogonal decompositions. SIAM J.
Sci. Statist. Comput., 4:261–269,
1983.
Hig85

Hen62
[Hen62]

C. S. Henkel, M. T. Heath, and
R. J. Plemmons. Cholesky downdating on a hypercube. In G. Fox,
editor, The Third Conference on
Hypercube Concurrent Computers and Applications, Vol. II,
Applications, pages 1592–1598.
ACM Press, New York, NY,
USA, 1988.

N. J. Higham. Nearness Problems in Numerical Linear Algebra. PhD thesis, University of
Manchester, UK, 1985.
Hig86a
N. J. Higham. Computing the polar decomposition with applications. SIAM J. Sci. Statist. Comput., 7:1160–1174, 1986.
Hig86b
N. J. Higham. Efficient algorithms for computing the condition number of a tridiagonal matrix. SIAM J. Sci. Statist. Comput., 7:150–165, 1986.

Golub and Van Loan: gvl.bib

50

Hig86c
[Hig86c]

Hig88e

N. J. Higham. Newton’s method [Hig88d]
for the matrix square root. Math.
Comp., 46:537–550, 1986.
Hig87a

[Hig87a]

[Hig87b]

N. J. Higham. Computing real
square roots of a real matrix.
Linear Algebra Appl., 88/89:405–
430, 1987.
[Hig88e]
Hig87b
N. J. Higham.
Error analysis of the Björck-Pereyra algorithms for solving Vandermonde
systems. Numer. Math., 50:613–
632, 1987.
Hig87c

[Hig87c]

N. J. Higham. A survey of condi- [Hig88f]
tion number estimation for triangular matrices. SIAM Rev., 29:
575–596, 1987.
N. J. Higham. The accuracy of [Hig89]
solutions to triangular systems.
Technical Report 158, Mathematics, University of Manchester,
UK, 1988.

N. J. Higham. Computing a nearest symmetric positive semidefinite matrix.
Linear Algebra
Appl., 103:103–118, 1988.

N. J. Higham. The symmetric
Procrustes problem. BIT, 28:
133–143, 1988.

N. J. Higham.
Analysis of
the Cholesky decomposition of a
semi-definite matrix. In M. G.
Cox and S. J. Hammarling, editors, Reliable Numerical Computation. Oxford University Press,
1989.
HocJ88

[HJ88]

Hig88c
[Hig88c]

N. J. Higham. Matrix nearness
problems and applications. Technical Report 161, Mathematics,
University of Manchester, UK,
1988. To appear in Proceedings
of the IMA Conference on Applications of Matrix Theory, eds. S.
Barnett and M. J. C. Gover.

Hig89

Hig88b
[Hig88b]

Hig88f

Hig88d

Hig88a
[Hig88a]

N. J. Higham. Fortran codes for
estimating the one-norm of a real
or complex matrix, with applications to condition estimation.
ACM Trans. Math. Software, 14:
381–396, 1988.

N. J. Higham.
Fast solution
of Vandermonde-like systems involving orthogonal polynomials. [HL69]
IMA J. Numer. Anal., 8:473–486,
1988.

R. W. Hockney and C. R.
Jesshope.
Parallel Computers
2. Adam Hilger, Bristol and
Philadelphia, 1988.
HanL69
R. J. Hanson and C. L. Lawson. Extensions and applications
of the Householder algorithm for

Golub and Van Loan: gvl.bib

51

J. Math. Statist. Psych., 10:69–
79, 1957.

solving linear least squares problems. Math. Comp., 23:787–812,
1969.

Hou58

HeaLPW86
[HLPW86] M. T. Heath, A. J. Laub, C. C.
Paige, and R. C. Ward. Computing the SVD of a product of two
matrices. SIAM J. Sci. Statist.
Comput., 7:1147–1159, 1986.
HanN81
[HN81]

R. J. Hanson and M. J. Norris.
Analysis of measurements based
on the singular value decomposition. SIAM J. Sci. Statist. Comput., 2:363–374, 1981.

[Hou58]

Hou68
[Hou68]

[Hou74]

D. Hoaglin. Mathematical software and exploratory data analysis. In John Rice, editor, Mathematical Software III, pages 139–
159. Academic Press, New York, [HP78]
NY, USA, 1977.
Hoc65

[Hoc65]

R. W. Hockney. A fast direct solution of Poisson’s equation using
Fourier analysis. J. Assoc. Comput. Mach., 12:95–113, 1965.
[HR88]
Hoc83

[Hoc83]

R. Hockney.
Characterizing
computers and optimizing the
FACR(`) Poisson solver on parallel unicomputers. IEEE Trans.
Comput., C-32:933–941, 1983.
Hot57

[Hot57]

H. Hotelling. The relations of
the newer multivariate statistical
methods to factor analysis. Brit.

A. S. Householder. Moments and
characteristic roots II. Numer.
Math., 11:126–128, 1968.
Hou74

Hoa77
[Hoa77]

A. S. Householder. Unitary triangularization of a nonsymmetric matrix. J. Assoc. Comput.
Mach., 5:339–342, 1958.

A. S. Householder. The Theory
of Matrices in Numerical Analysis. Dover Publications, New
York, NY, USA, 1974.
HofP78
W. Hoffmann and B. N. Parlett.
A new proof of global convergence for the tridiagonal QL algorithm. SIAM J. Numer. Anal.,
15:929–937, 1978.
HeaR88
M. T. Heath and C. H. Romine.
Parallel solution of triangular
systems on distributed memory multiprocessors. SIAM J.
Sci. Statist. Comput., 9:558–588,
1988.
HesS52

[HS52]

M. R. Hestenes and E. Stiefel.
Methods of conjugate gradients
for solving linear systems. J. Res.
Nat. Bur. Standards, 49:409–436,
1952.

Golub and Van Loan: gvl.bib

52

HulS66
[HS66]

T. E. Hull and J. R. Swenson. [Huf88]
Tests of probabilistic models for
propagation of roundoff errors.
Comm. ACM, 9:108–113, 1966.
HeaS86

[HS86]

M. T. Heath and D. C. Sorensen.
A pipelined method for computing the QR factorization of a [HV87]
sparse matrix. Linear Algebra
Appl., 77:189–203, 1986.
HigS88

[HS88]

N. J. Higham and R. S. Schreiber.
Fast polar decomposition of an
arbitrary matrix. Technical Report 88-942, Computer Science, [HV88a]
Cornell University, Ithaca, NY
14853, 1988.
Hua75

Huf88
S. Van Huffel. Comments on the
solution of the nongeneric total
least squares problem. Technical Report ESAT-KUL-88/3, Department of Electrical Engineering, Katholieke Universiteit Leuven, Leuven, Belgium, 1988.
HufV87
S. Van Huffel and J. Vandewalle. Subset selection using the
total least squares approach in
collinearity problems with errors
in the variables. Linear Algebra
Appl., 88/89:695–714, 1987.
HufV88a
S. Van Huffel and J. Vandewalle.
The partial total least squares
algorithm.
J. Comput. Appl.
Math., 21:333–342, 1988.
HufV88b

[Hua75]

C. P. Huang.
A Jacobi-type
method for triangularizing an ar- [HV88b]
bitrary matrix. SIAM J. Numer.
Anal., 12:566–570, 1975.
Hua81

[Hua81]

C. P. Huang. On the conver- [HVH87]
gence of the QR algorithm with
origin shifts for normal matrices.
IMA J. Numer. Anal., 1:127–133,
1981.
Huf87

[Huf87]

S. Van Huffel. Analysis of the
Total Least Squares Problem and
Its Use in Parameter Estimation. [HY81]
PhD thesis, Electrical Engineering, Katholieke Universiteit Leuven, Leuven, Belgium, 1987.

S. Van Huffel and J. Vandewalle.
The partial total least squares
algorithm.
J. Comput. Appl.
Math., 21:333–342, 1988.
HufVH87
S. Van Huffel, J. Vandewalle, and
A. Haegemans. An efficient and
reliable algorithm for computing
the singular subspace of a matrix
associated with its smallest singular values. J. Comput. Appl.
Math., 19:313–330, 1987.
HagY81
L. A. Hageman and D. M. Young.
Applied Iterative Methods. Academic Press, New York, NY,
USA, 1981.

Golub and Van Loan: gvl.bib

53

gradient method. J. Inst. Math.
Appl., 20:61–72, 1977.

HenZ68
[HZ68]

P. Henrici and K. Zimmermann.
An estimate for the norms of
certain cyclic Jacobi operators.
[Jen77b]
Linear Algebra Appl., 1:489–501,
1968.
Ike79

[Ike79]

Y. Ikebe. On inverses of Hessenberg matrices. Linear Algebra
Appl., 24:93–97, 1979.

[JH87a]

A. Iserles and M. J. D. Powell,
editors. The State of the Art in
Numerical Analysis. Oxford University Press, 1987.
IpsSS86

[ISS86]

I. C. F. Ipsen, Y. Saad, and
M. Schultz. Dense linear systems
on a ring of processors. Linear
Algebra Appl., 77:205–239, 1986.

[JH87b]

C. G. J. Jacobi. Über ein leichtes verfahren die in der theorie der säculärstörungen vorkommenden gleichungen numerisch
aufzulösen. Crelle’s J., 30:51–94, [JH88]
1846.
Jen72

[Jen72]

P. S. Jenson. The solution of
large symmetric eigenproblems
by sectioning. SIAM J. Numer.
Anal., 9:534–545, 1972.
Jen77a

[Jen77a]

A. Jennings. Influence of the
eigenvalue spectrum on the convergence rate of the conjugate

S. L. Johnsson and C. T. Ho. Algorithms for multiplying matrices
of arbitrary shapes using shared
memory primatives on a Boolean
cube. Technical Report YALEU
DCS RR-569, Computer Science,
Yale University, New Haven, CT,
USA, 1987.
JohH87c

Jac46
[Jac46]

A. Jennings. Matrix Computation for Engineers and Scientists.
John Wiley and Sons, New York,
NY, USA, 1977.
JohH87

IseP87
[IP87]

Jen77b

S. L. Johnsson and C. T. Ho.
Multiple tridiagonal systems, the
alternating direction methods,
and Boolean cube configured
multiprocessors. Technical Report YALEU DCS RR-532, Computer Science, Yale University,
New Haven, CT, USA, 1987.
JohH88
S. L. Johnsson and C. T. Ho. Algorithms for matrix transposition
on Boolean N -cube configured
ensemble architectures. SIAM J.
Matrix Anal. Appl., 9:419–454,
1988.
JohMP83

[JMP83]

O. G. Johnson, C. A. Micchelli,
and G. Paul. Polynomial preconditioners for conjugate gradient
calculations. SIAM J. Numer.
Anal., 20:362–376, 1983.

Golub and Van Loan: gvl.bib

54

JenO71
[JO71]

A. Jennings and D. R. L. Orr. [Joh86]
Application of the simultaneous
iteration method to undamped
vibration problems. Internat. J.
Numer. Methods Engrg., 3:13–24,
1971.
JenO74

[JO74]

L. S. Jennings and M. R. Osborne. A direct error analysis for
least squares. Numer. Math., 22:
[Joh87a]
322–332, 1974.
JenO77

[JO77]

A. Jennings and M. R. Osborne.
Generalized eigenvalue problems
for certain unsymmetric band
matrices. Linear Algebra Appl., [Joh87b]
29:139–150, 1977.
Joh71

[Joh71]

R. L. Johnston. Gershgorin theorems for partitioned matrices.
Linear Algebra Appl., 4:205–220, [Jor84]
1971.
Joh84

[Joh84]

S. L. Johnsson. Odd-even cyclic
reduction on ensemble architectures and the solution of tridiagonal systems of equations. Technical Report YALEU DCS RR-339,
Computer Science, Yale Univer- [Jor87]
sity, New Haven, CT, USA, 1984.
Joh85

[Joh85]

S. L. Johnsson. Solving narrow
banded systems on ensemble architectures. ACM Trans. Math. [JP71]
Software, 11:271–288, 1985.

Joh86
S. L. Johnsson. Band matrix
system solvers on ensemble architectures. In F. A. Matsen
and T. Tajima, editors, Supercomputers: Algorithms, Architectures, and Scientific Computation, pages 196–216. University of
Texas Press, Austin, TX, USA,
1986.
Joh87a
S. L. Johnsson.
Communication efficient basic linear algebra
computations on hypercube multiprocessors. J. Parallel and Distrib. Comput., 4:133–172, 1987.
Joh87b
S. L. Johnsson. Solving tridiagonal systems on ensemble architectures. SIAM J. Sci. Statist. Comput., 8:354–392, 1987.
Jor84
T. Jordan. Conjugate gradient
preconditioners for vector and
parallel processors. In G. Birkoff
and A. Schoenstadt, editors, Proceedings of the Conference on Elliptic Problem Solvers. Academic
Press, New York, NY, USA,
1984.
Jor87
H. Jordan. Interpreting parallel processor performance measurements. SIAM J. Sci. Statist.
Comput., 8:s220–s226, 1987.
JohP71
J. Johnson and C. L. Phillips. An
algorithm for the computation of

Golub and Van Loan: gvl.bib

55

the integral of the state transition
matrix. IEEE Trans. Automat.
[Kåg85]
Control, AC-16:204–205, 1971.
JenS75
[JS75]

A. Jennings and W. J. Stewart. Simultaneous iteration for
the partial eigensolution of real
[Kåg86]
matrices. J. Inst. Math. Appl.,
15:351–362, 1975.
DenT87

[JT87]

J. E. Dennis Jr and K. Turner.
Generalized conjugate directions.
Linear Algebra Appl., 88/89:187–
209, 1987.

M. Jankowski and M. Wozniakowski. Iterative refinement implies numerical stability. BIT, 17:
303–311, 1977.

[Kah66]

[Kah67]

K. C. Jea and D. M. Young.
On the simplification of generalized conjugate gradient methods for nonsymmetrizable linear [Kah75]
systems. Linear Algebra Appl.,
52/53:399–417, 1983.

B. Kågström. Bounds and perturbation bounds for the matrix exponential. BIT, 17:39–57,
1977.

[Kan66]

Kag77b
[Kåg77b]

B. Kågström. RGSVD: An algorithm for computing the Kronecker structure and reducing
subspaces of singular A−λB pencils. SIAM J. Sci. Statist. Comput., 7:185–211, 1986.

W. Kahan. Numerical linear algebra. Canad. Math. Bull., 9:757–
801, 1966.

W. Kahan.
Inclusion theorems for clusters of eigenvalues
of Hermitian matrices. report,
Computer Science, University of
Toronto, Toronto, Canada, 1967.
Kah75
W. Kahan. Spectra of nearly
Hermitian matrices. Proc. Amer.
Math. Soc., 48:11–17, 1975.
Kan66

Kag77a
[Kåg77a]

Kag86

Kah67

JeaY83
[JY83]

B. Kågström. The generalized
singular value decomposition and
the general A−λB problem. BIT,
24:568–583, 1985.

Kah66

JanW77
[JW77]

Kag85

B. Kågström. Numerical compu- [Kar74]
tation of matrix functions. Technical Report UMINF-58.77, Information Processing, University
of Umeå, Umeå, Sweden, 1977.

S. Kaniel. Estimates for some
computational techniques in linear algebra. Math. Comp., 20:
369–378, 1966.
Kar74
I. Karasalo. A criterion for truncation of the QR decomposition
algorithm for the singular linear
least squares problem. BIT, 14:
156–166, 1974.

Golub and Van Loan: gvl.bib

56

Kat66
[Kat66]

T. Kato. Perturbation Theory
for Linear Operators. SpringerVerlag, New York, NY, USA,
[KdV77]
1966.
Kau74

[Kau74]

L. Kaufman. The LZ algorithm
to solve the generalized eigenvalue problem. SIAM J. Numer.
Anal., 11:997–1024, 1974.
Kau77

[Kau77]

L. Kaufman. Some thoughts on
the QZ algorithm for solving the [Ker82]
generalized eigenvalue problem.
ACM Trans. Math. Software, 3:
65–75, 1977.
Kau79

[Kau79]

L. Kaufman.
Application of
dense Householder transformations to a sparse matrix. ACM
Trans. Math. Software, 5:442–
[KF64]
450, 1979.
Kau83

[Kau83]

L. Kaufman. Matrix methods
for queueing problems. SIAM J.
Sci. Statist. Comput., 4:525–552,
1983.

Sci. Statist. Comput., 5:701–719,
1984.
KatdV77
J. M. Van Kats and H. A. Van
der Vorst. Automatic monitoring of Lanczos schemes for symmetric or skew-symmetric generalized eigenvalue problems. Technical Report TR 7, Academische
Computer Centre, Utrecht, The
Netherlands, 1977.
Ker82
D. Kershaw. Solution of single tridiagonal linear systems and
vectorization of the ICCG algorithm on the Cray-1.
In
G. Roderigue, editor, Parallel
Computation. Academic Press,
New York, NY, USA, 1982.
KubF64
V. N. Kublanovskaya and V. N.
Fadeeva. Computational methods for the solution of a generalized eigenvalue problem. Amer.
Math. Soc. Transl., 2:271–290,
1964.
KauG83

Kau87
[Kau87]

L. Kaufman. The generalized
Householder transformation and
sparse matrices. Linear Algebra
Appl., 90:221–234, 1987.

[KG83]

Kie87

KapB84
[KB84]

R. N. Kapur and J. C. Browne.
Techniques for solving block
tridiagonal systems on reconfigurable array computers. SIAM J.

J. Kautsky and G. H. Golub. On
the calculation of Jacobi matrices. Linear Algebra Appl., 52/53:
439–456, 1983.

[Kie87]

A. Kielbasinski. A note on rounding error analysis of Cholesky factorization. Linear Algebra Appl.,
88/89:487–494, 1987.

Golub and Van Loan: gvl.bib

57

KagL88
[KL88]

B. Kågström and P. Ling. Level
2 and 3 BLAS routines for the
IBM 3090 VF/400: Implementation and experiences. Technical Report UMINF-154.88, Information Processing, University of
Umeå, S-901 87 Umeå, Sweden,
[Knu81]
1988.
KriM86a

[KM86a]

A. S. Krishnakuma and M. Morf.
Eigenvalues of a symmetric tridiagonal matrix: A divide and conquer approach. Numer. Math.,
[Kog55]
48:349–368, 1986.
KulM86b

[KM86b]

U. W. Kulisch and W. L. Miranker. The arithmetic of the digital computer. SIAM Rev., 28:1–
[KP74]
40, 1986.
KahMN88

[KMN88]

D. Kahaner, C. B. Moler, and
S. Nash. Numerical Methods and
Software. Prentice-Hall, Englewood Cliffs, NJ, USA, 1988.
KagNP87

[KNP87]

[KNP88]

B. Kågström, L. Nyström, and
P. Poromaa.
Parallel shared

Knu81
D. Knuth.
SeminumericalAlgorithms, volume 2 of The
Art of Computer Programming.
Addison-Wesley, Reading, MA,
USA, second edition, 1981.
Kog55
E. G. Kogbetliantz. Solution of
linear equations by diagonalization of coefficient matrix. Quart.
Appl. Math., 13:123–132, 1955.
KahP74
W. Kahan and B. N. Parlett. An
analysis of Lanczos algorithms
for symmetric matrices. Technical Report ERL-M467, University of California, Berkeley,
Berkeley, CA, USA, 1974.
KahP76

[KP76]

B. Kågström, L. Nyström, and
P. Poromaa.
Parallel algorithms for solving the triangular Sylvester equation on a hypercube multiprocessor. Technical Report UMINF-136.87, Information Processing, University of
Umeå, S-901 87 Umeå, Sweden,
[KP81]
1987.
KagNP88

memory algorithms for solving
the triangular Sylvester equation. Technical Report UMINF155.88, Information Processing,
University of Umeå, S-901 87
Umeå, Sweden, 1988.

W. Kahan and B. N. Parlett.
How far should you go with the
Lanczos process? In J. Bunch
and D. Rose, editors, Sparse Matrix Computations, pages 131–
144. Academic Press, New York,
NY, USA, 1976.
KouP81
S. Kourouklis and C. C. Paige.
A constrained least squares approach to the general GaussMarkov linear model. J. Amer.
Statist. Assoc., 76:620–625, 1981.

Golub and Van Loan: gvl.bib

58

KahPJ82
[KPJ82]

KagW87

W. Kahan, B. N. Parlett, and [KW87]
E. Jiang. Residual bounds on approximate eigensystems of nonnormal matrices. SIAM J. Numer. Anal., 19:470–484, 1982.
KagR80a

[KR80a]

B. Kågström and A. Ruhe. Algorithm 560 JNF: An algorithm
for numerical computation of the
Jordan normal form of a complex
matrix. ACM Trans. Math. Soft- [Lan50]
ware, 6:437–443, 1980.
KagR80b

[KR80b]

B. Kågström and A. Ruhe. An
algorithm for numerical computation of the Jordan normal form
of a complex matrix. ACM Trans.
Math. Software, 6:398–419, 1980. [Lan70]
KagR83

[KR83]

B. Kågström and A. Ruhe, editors. Proceedings of the Con[Lau81]
ference on Matrix Pencils, Pite
Havsbad 1982, volume 973 of
Lecture Notes in Mathematics.
Springer-Verlag, New York and
Berlin, 1983.
Kub61

[Kub61]

V. N. Kublanovskaya. On some
algorithms for the solution of
the complete eigenvalue problem.
U. S. S. R. Comput. Math. and
Math. Phys., 3:637–657, 1961.
Kun82

[Kun82]

[Lau85]

H. T. Kung. Why systolic architectures? IEEE Computer, 15:
37–46, 1982.

B. Kågström and L. Westin.
GSYLV- Fortran routines for
the generalized Schur method
with dif−1 estimators for solving
the generalized Sylvester equation. Technical Report UMINF132.86, Information Processing,
University of Umeå, S-901 87
Umeå, Sweden, 1987.
Lan50
C. Lanczos. An iteration method
for the solution of the eigenvalue problem of linear differential and integral operators. J.
Res. Nat. Bur. Standards, 45:
255–282, 1950.
Lan70
P. Lancaster. Explicit solution of
linear matrix equations. SIAM
Rev., 12:544–566, 1970.
Lau81
A. Laub.
Efficient multivariable frequency response computations. IEEE Trans. Automat.
Control, AC-26:407–408, 1981.
Lau85
A. Laub. Numerical linear algebra aspects of control design
computations. IEEE Trans. Automat. Control, AC-30:97–108,
1985.
LiC88

[LC88]

G. Li and T. Coleman.
A
parallel triangular solver for a
distributed-memory multiprocessor. SIAM J. Sci. Statist. Comput., 9:485–502, 1988.

Golub and Van Loan: gvl.bib

59

LawHKK79a

Leh63
[Leh63]

N. J. Lehmann. Optimale Eigenwerteinschliessungen.
Numer.
Math., 5:246–272, 1963.
Lem73

[Lem73]

[Leo80]

[Lev47]

[Lew77]

[LHKK79a] C. L. Lawson, R. J. Hanson,
D. R. Kincaid, and F. T. Krogh.
Algorithm 539: Basic linear algebra subprograms for Fortran usage. ACM Trans. Math. Software, 5:324–325, 1979.

F. Lemeire. Bounds for condition numbers of triangular and
LawHKK79b
trapezoid matrices. BIT, 15:58–
64, 1973.
[LHKK79b] C. L. Lawson, R. J. Hanson,
D. R. Kincaid, and F. T. Krogh.
Leo80
Basic linear algebra subprograms
S. J. Leon. Linear Algebra with
for Fortran usage. ACM Trans.
Applications. Macmillan, New
Math. Software, 5:308–323, 1979.
York, NY, USA, 1980.
Lin61
Lev47
[Lin61]
I. Linnik.
Method of Least
N. Levinson. The Weiner RMS
Squares and Principles of the
error criterion in filter design and
Theory of Observation. Pergaprediction. J. Math. Phys., 25:
mon Press, New York, NY, USA,
261–278, 1947.
1961.
Lew77
LusO83
J. Lewis.
Algorithms for [LO83]
sparse matrix eigenvalue problems. Technical Report STANCS-77-595, Department of Computer Science, Stanford University, Stanford, CA, USA, 1977.
LawH69

[LH69]

C. L. Lawson and R. J. Hanson. Extensions and applications
[Loa73]
of the Householder algorithm for
solving linear least squares problems. Math. Comp., 23:787–812,
1969.
LawH74

[LH74]

C. L. Lawson and R. J. Hanson.
Solving Least Squares Problems.
Prentice-Hall, Englewood Cliffs,
NJ, USA, 1974.

E. Lusk and R. Overbeek. Implementation of monitors with
macros: A programming aid for
the HEP and other parallel processors. Technical Report 8397, Argonne National Laboratory, Argonne, ILL, 1983.
Loa73
C. F. Van Loan. Generalized Singular Values with Algorithms and
Applications. PhD thesis, University of Michigan, Ann Arbor, MI,
USA, 1973.
Loa75a

[Loa75a]

C. F. Van Loan. A general matrix
eigenvalue algorithm. SIAM J.
Numer. Anal., 12:819–834, 1975.

Golub and Van Loan: gvl.bib

60

Loa75b
[Loa75b]

Loa82

C. F. Van Loan. A study of [Loa82]
the matrix exponential. Technical Report 10, Numerical Analysis, University of Manchester,
UK, 1975.
Loa76

[Loa76]

C. F. Van Loan. Generalizing
the singular value decomposition.
SIAM J. Numer. Anal., 13:76–
83, 1976.
[Loa83]
Loa77a

[Loa77a]

C. F. Van Loan. On the limitation and application of the Padé
approximation to the matrix exponential. In E. B. Saff and R. S.
Varga, editors, Padé and Rational Approximation. Academic
Press, New York, NY, USA,
[Loa84]
1977.
Loa77b

[Loa77b]

C. F. Van Loan. The sensitivity of the matrix exponential.
SIAM J. Numer. Anal., 14:971–
981, 1977.

[Loa85a]

C. F. Van Loan. Computing integrals involving the matrix exponential. IEEE Trans. Automat.
[Loa85b]
Control, AC-23:395–404, 1978.
Loa78b

[Loa78b]

Loa83
C. F. Van Loan. A generalized
SVD analysis of some weighting
methods for equality-constrained
least squares. In B. Kågström
and A. Ruhe, editors, Proceedings
of the Conference on Matrix Pencils. Springer-Verlag, New York,
NY, USA, 1983.
Loa84
C. F. Van Loan. A symplectic
method for approximating all the
eigenvalues of a Hamiltonian matrix. Linear Algebra Appl., 61:
233–252, 1984.
Loa85a

Loa78a
[Loa78a]

C. F. Van Loan. Using the Hessenberg decomposition in control
theory. In D. C. Sorensen and
R. J. Wets, editors, Algorithms
and Theory in Filtering and Control, number 18 in Mathematical
Programming Study, pages 102–
111. North-Holland, Amsterdam,
The Netherlands, 1982.

C. F. Van Loan. A note on the
evaluation of matrix polynomials.
IEEE Trans. Automat. Control, [Loa85c]
AC-24:320–321, 1978.

C. F. Van Loan. Computing the
CS and generalized singular value
decomposition. Numer. Math.,
46:479–492, 1985.
Loa85b
C. F. Van Loan. How near is a
stable matrix to an unstable matrix? Contemp. Math., 47:465–
477, 1985.
Loa85c
C. F. Van Loan. On the method
of weighting for equality con-

Golub and Van Loan: gvl.bib

61

Academic Press, New York, NY,
USA, second edition, 1985.

strained least squares problems.
SIAM J. Numer. Anal., 22:851–
864, 1985.
Loa87
[Loa87]

[Lue73]

C. F. Van Loan. On estimating the condition of eigenvalues
and eigenvectors. Linear Algebra
Appl., 88/89:715–732, 1987.
Loi69

[Loi69]

Lue73

Luk78
[Luk78]

F. T. Luk. Sparse and Parallel
Matrix Computations. PhD thesis, Computer Science, Stanford
University, Stanford, CA, USA,
1978.
Luk80

G. Loizou. On the quadratic con- [Luk80]
vergence of the Jacobi method for
normal matrices. Comput. J., 15:
274–276, 1972.

F. T. Luk. Computing the singular value decomposition on the
ILLIAC IV. ACM Trans. Math.
Software, 6:524–539, 1980.

G. Loizou. Nonnormality and
Jordan condition numbers of matrices. J. Assoc. Comput. Mach.,
16:580–584, 1969.
Loi72

[Loi72]

Luk86a

Lot56
[Lot56]

D. G. Luenberger. Introduction
to Linear and Nonlinear Programming. Addison-Wesley, New
York, NY, USA, 1973.

M. Lotkin. Characteristic values of arbitrary matrices. Quart.
Appl. Math., 14:267–275, 1956.

[Luk86a]

LoPS87

F. T. Luk. A rotation method for
computing the QR factorization.
SIAM J. Sci. Statist. Comput., 7:
452–459, 1986.
Luk86b

[LPS87]

[LS78]

S. Lo, B. Philippe, and A. Sameh.
A multiprocessor algorithm for
the symmetric tridiagonal eigenvalue problem. SIAM J. Sci.
Statist. Comput., 8:s155–s165,
1987.
LarS78

[Luk86b]

LamV75
[LV75]

J. Larson and A. Sameh. Efficient calculation of the effects
of roundoff errors. ACM Trans.
Math. Software, 4:228–236, 1978.

P. Lancaster and M. Tismenetsky. The Theory of Matrices.

J. Lambiotte and R. G. Voigt.
The solution of tridiagonal linear
systems on the CDC-STAR 100
computer. ACM Trans. Math.
Software, 1:308–329, 1975.
Mad59

LanT85
[LT85]

F. T. Luk. A triangular processor array for computing singular
values. Linear Algebra Appl., 77:
259–274, 1986.

[Mad59]

A. Madansky. The fitting of
straight lines when both variables

Golub and Van Loan: gvl.bib

62

are subject to error. J. Amer.
Statist. Assoc., 54:173–205, 1959.

McK62
[McK62]

Mah79
[Mah79]

K. N. Mahindar. Linear combinations of Hermitian and real symmetric matrices. Linear Algebra
Appl., 25:95–105, 1979.

MdV77
[MdV77]

Mak75
[Mak75]

J. Makhoul. Linear prediction:
A tutorial review. Proc. IEEE,
63(4):561–580, 1975.
Man77

[Man77]

T. A. Manteuffel. The Tchebychev iteration for nonsymmetric
linear systems. Numer. Math.,
28:307–327, 1977.

[Mei83]

[Mel87]

T. A. Manteuffel. Shifted incomplete Cholesky factorization. In
I. S. Duff and G. W. Stewart,
editors, Sparse Matrix Proceedings 1978. SIAM Publications,
[Mer85]
Philadelphia, PA, USA, 1979.

J. J. Modi and M. R. B. Clarke.
An alternative Givens ordering.
Numer. Math., 43:83–90, 1986.

R. Melhem. Toward efficient implementation of preconditioned
conjugate gradient methods on
vector supercomputers. Internat.
J. Supercomputing Applic., 1:70–
98, 1987.
Mer85
M. L. Merriam. On the factorization of block tridiagonals with
storage constraints. SIAM J.
Sci. Statist. Comput., 6:182–192,
1985.
Meu84

[Meu84]

McC72
[McC72]

J. Meinguet. Refined error analyses of Cholesky factorization.
SIAM J. Numer. Anal., 20:1243–
1250, 1983.
Mel87

ModC86
[MC86]

J. A. Meijerink and H. A. Van
der Vorst. An iterative solution
method for linear equations systems of which the coefficient matrix is a symmetric M -matrix.
Math. Comp., 31:148–162, 1977.
Mei83

Man79
[Man79]

W. M. McKeeman.
Crout
with equilibration and iteration.
Comm. ACM, 5:553–555, 1962.

S. F. McCormick.
A general approach to one-step iterative methods with application to
eigenvalue problems. J. Comput. [Meu89]
System Sci., 6:354–372, 1972.

G. Meurant.
The block preconditioned conjugate gradient
method on vector computers.
BIT, 24:623–633, 1984.
Meu89
G. Meurant. Domain decomposition methods for partial differen-

Golub and Van Loan: gvl.bib

63

Guide. 20 N. Main St., Sherborn,
MA, USA, 1987.

tial equations on parallel computers. Internat. J. Supercomputing
Applic., 1989. To appear.
MarG76
[MG76]

[MM64]

J. Markel and A. Gray. Linear
Prediction of Speech. SpringerVerlag, Berlin and New York,
1976.
Mil75

[Mil75]

MarM64

MolM83
[MM83]

W. Miller. Computational complexity and numerical stability.
SIAM J. Comput., 4:97–107,
1975.
L. Mirsky. An Introduction to
Linear Algebra. Oxford University Press, London, UK, 1955.

[Mod88]

Mir60
[Mir60]

L. Mirsky.
Symmetric gauge [Mol67]
functions and unitarily invariant
norms. Quart. J. Math. Oxford
Ser. (2), 11:50–59, 1960.
MolL78

[ML78]

[Mol80]

C. B. Moler and C. F. Van Loan.
Nineteen dubious ways to compute the exponential of a matrix.
SIAM Rev., 20:801–836, 1978.
MonL82

[ML82]

R. Montoye and D. Laurie. A [Mol86]
practical algorithm for the solution of triangular systems on
a parallel processing system.
IEEE Trans. Comput., C-31:
1076–1082, 1982.

C. B. Moler, J. N. Little, and
S. Bangert. PC-Matlab Users

J. J. Modi. Parallel Algorithms
and Matrix Computation. Oxford
University Press, Oxford, UK,
1988.
Mol67
C. B. Moler. Iterative refinement
in floating point. J. Assoc. Comput. Mach., 14:316–371, 1967.
Mol80
C. B. Moler. MATLAB user’s
guide. Technical Report CS81-1,
Computer Science, University of
New Mexico, Albuquerque, NM,
USA, 1980.
Mol86

MolLB87
[MLB87]

C. B. Moler and D. Morrison.
Singular value analysis of cryptograms. Amer. Math. Monthly,
90:78–87, 1983.
Mod88

Mir55
[Mir55]

M. Marcus and H. Minc. A Survey of Matrix Theory and Matrix
Inequalities. Allyn and Bacon,
Boston, MA, USA, 1964.

C. B. Moler.
Matrix computations on distributed memory multiprocessors. In M. T.
Heath, editor, Hypercube Multiprocessors. SIAM Publications,
Philadelphia, PA, USA, 1986.
MalP74

[MP74]

M. A. Malcolm and J. Palmer.
A fast method for solving a class

Golub and Van Loan: gvl.bib

64

of tridiagonal systems of linear
equations. Comm. ACM, 17:14–
17, 1974.

MadRK76
[MRK76]

MimP82
[MP82]

G. Miminis and C. C. Paige. An
algorithm for pole assignment of
time invariant linear systems. Internat. J. Control, 35:341–354, [MRW70]
1982.
ModP85

[MP85]

J. J. Modi and J. D. Pryce. Efficient implementation of Jacobi’s
diagonalization method on the
DAP. Numer. Math., 46:443–454,
[MS73a]
1985.
MarPW65

[MPW65]

R. S. Martin, G. Peters, and J. H.
Wilkinson. Symmetric decomposition of a positive definite ma- [MS73b]
trix. Numer. Math., 7:362–383,
1965. Also in [WR71, pages 9–
30].
MarPW66

N. Madsen, G. Roderigue, and
J. Karush. Matrix multiplication
by diagonals of a vector parallel
processor. Inform. Process. Lett.,
pages 41–45, 1976.
MarRW70
R. S. Martin, C. Reinsch, and
J. H. Wilkinson. The QR algorithm for band symmetric matrices. Numer. Math., 16:85–92,
1970. Also in [WR71, pages 266–
272].
McCS73a
C. McCarthy and G. Strang. Optimal conditioning of matrices.
SIAM J. Numer. Anal., 10:370–
388, 1973.
MolS73b
C. B. Moler and G. W. Stewart. An algorithm for generalized matrix eigenvalue problems.
SIAM J. Numer. Anal., 10:241–
256, 1973.
MilS78

[MPW66]

R. S. Martin, G. Peters, and J. H.
Wilkinson. Iterative refinement [MS78]
of the solution of a positive definite system of equations. Numer.
Math., 8:203–216, 1966. Also in
[WR71, pages 31–44].
MarPW70

[MPW70]

[Mue66]

R. S. Martin, G. Peters, and
J. H. Wilkinson. The QR algorithm for real Hessenberg matrices. Numer. Math., 14:219–231,
1970. Also in [WR71, pages 359– [MvdV87]
371].

W. Miller and D. Spooner. Software for roundoff analysis, II.
ACM Trans. Math. Software, 4:
369–390, 1978.
Mue66
D. Mueller.
Householder’s
method for complex matrices and
Hermitian matrices.
Numer.
Math., 8:72–92, 1966.
MvdV87
O. McBryan and E. F. van de
Velde.
Hypercube algorithms

Golub and Van Loan: gvl.bib

65

and implementations. SIAM J.
Sci. Statist. Comput., 8:s227–
s287, 1987.

MarW68c
[MW68c]

MurW31
[MW31]

F. D. Murnaghan and A. Wintner. A canonical form for real
matrices under orthogonal transformations. Proc. Nat. Acad. Sci. [MW68d]
U. S. A., 17:417–420, 1931.
MarW65

[MW65]

R. S. Martin and J. H. Wilkinson. Symmetric decomposition of
positive definite band matrices.
Numer. Math., 7:355–361, 1965. [Nan85]
Also in [WR71, pages 50–56].
MarW67

[MW67]

R. S. Martin and J. H. Wilkinson.
Similarity reduction of a general
matrix to Hessenberg form. Numer. Math., 12:349–368, 1968.
Also in [WR71, pages 339–358].
Nan85
T. Nanda. Differential equations
and the QR algorithm. SIAM J.
Numer. Anal., 22:310–321, 1985.
Nas75
J. C. Nash. A one-sided transformation method for the singular value decomposition and algebraic eigenproblem. Comput. J.,
18:74–76, 1975.

[Nas76]

M. Z. Nashed. Generalized Inverses and Applications. Academic Press, New York, NY,
USA, 1976.

R. S. Martin and J. H. Wilkinson. Householder’s tridiagonalization of a symmetric matrix.
Numer. Math., 11:181–195, 1968.
[ND77]
Also in [WR71, pages 212–226].
MarW68b

[MW68b]

MarW68d

R. S. Martin and J. H. Wilkin- [Nas75]
son. Solution of symmetric and
unsymmetric band equations and
the calculation of eigenvalues of
band matrices. Numer. Math., 9:
279–301, 1967. Also in [WR71,
pages 70–92].
MarW68a

[MW68a]

R. S. Martin and J. H. Wilkinson. Reduction of the symmetric
eigenproblem Ax = λBx and related problems to standard form.
Numer. Math., 11:99–110, 1968.

R. S. Martin and J. H. Wilkinson. The modified LR algorithm
for complex Hessenberg matrices. [Nic74]
Numer. Math., 12:369–376, 1968.
Also in [WR71, pages 396–403].

Nas76

NobD77
B. Noble and J. W. Daniel. Applied Linear Algebra. PrenticeHall, Englewood Cliffs, NJ, USA,
1977.
Nic74
R. A. Nicolaides. On a geometrical aspect of SOR and the theory
of consistent ordering for positive

Golub and Van Loan: gvl.bib

66

definite matrices. Numer. Math.,
23:99–104, 1974.

Opp78
[Opp78]

NooV75
[NV75]

A. Noor and R. Voigt. Hypermatrix scheme for the STAR-100
computer. Comput. & Structures,
5:287–296, 1975.

OrtR88
[OR88]

NieV83
[NV83]

W. Niethammer and R. S. Varga.
The analysis of k-step iterative
methods for linear systems from
summability theory.
Numer.
Math., 41:177–206, 1983.
[Ort72]
OLe76

[O’L76]

D. P. O’Leary. Hybrid Conjugate
Gradient Algorithms. PhD thesis, Computer Science, Stanford
University, Stanford, CA, USA, [Ort88]
1976.
OLe80a

[O’L80a]

D. P. O’Leary. The block conjugate gradient algorithm and re- [OS81]
lated methods. Linear Algebra
Appl., 29:293–322, 1980.
OLe80b

[O’L80b]

D. P. O’Leary. Estimating matrix condition numbers. SIAM J.
Sci. Statist. Comput., 1:205–209,
[OS85]
1980.
OetP64

[OP64]

A. V. Oppenheim.
Applications of Digital Signal Processing.
Prentice-Hall, Englewood Cliffs,
NJ, USA, 1978.

W. Oettli and W. Prager. Compatibility of approximate solutions of linear equations with
given error bounds for coefficients [OS86]
and right hand sides. Numer.
Math., 6:405–409, 1964.

J. M. Ortega and C. H. Romine.
The ijk forms of factorization methods II: Parallel systems. Parallel Comput., 7:149–
162, 1988.
Ort72
J. M. Ortega. Numerical Analysis: A Second Course. Academic Press, New York, NY,
USA, 1972.
Ort88
J. M. Ortega. Matrix Theory: A
Second Course. Plenum Press,
New York, NY, USA, 1988.
OLeS81
D. P. O’Leary and J. A. Simmons. A bidiagonalization - regularization procedure for large
scale discretizations of ill-posed
problems. SIAM J. Sci. Statist.
Comput., 2:474–489, 1981.
OLeS85
D. P. O’Leary and G. W. Stewart.
Data flow algorithms
for parallel matrix computations.
Comm. ACM, 28:841–853, 1985.
OLeS86
D. P. O’Leary and G. W. Stewart. Assignment and scheduling in parallel matrix factoriza-

Golub and Van Loan: gvl.bib

67

ear equations. SIAM J. Numer.
Anal., 11:197–209, 1974.

tion. Linear Algebra Appl., 77:
275–300, 1986.
Osb60
[Osb60]

Pai74b

E. E. Osborne. On precondition- [Pai74b]
ing of matrices. J. Assoc. Comput. Mach., 7:338–345, 1960.
OrtV85

[OV85]

Pai76

J. M. Ortega and R. G. Voigt. Solution of partial differential equa- [Pai76]
tions on vector and parallel computers. SIAM Rev., 27:149–240,
1985.
Paa71

[Paa71]

M. H. C. Paardekooper.
An
eigenvalue algorithm for skew
symmetric matrices.
Numer.
Math., 17:189–202, 1971.

[Pai79a]

C. C. Paige. Practical use of
the symmetric Lanczos process
[Pai79b]
with reorthogonalization. BIT,
10:183–195, 1970.
Pai71

[Pai71]

C. C. Paige. The Computation of
Eigenvalues and Eigenvectors of
Very Large Sparse Matrices. PhD
thesis, London University, Lon- [Pai80]
don, UK, 1971.
Pai73

[Pai73]

C. C. Paige. An error analysis
of a method for solving matrix
equations. Math. Comp., 27:355–
359, 1973.
[Pai81]
Pai74a

[Pai74a]

C. C. Paige. Bidiagonalization
of matrices and solution of lin-

C. C. Paige. Error analysis of
the Lanczos algorithm for tridiagonalizing a symmetric matrix.
J. Inst. Math. Appl., 18:341–349,
1976.
Pai79a

Pai70
[Pai70]

C. C. Paige. Eigenvalues of perturbed Hermitian matrices. Linear Algebra Appl., 8:1–10, 1974.

C. C. Paige. Computer solution
and perturbation analysis of generalized least squares problems.
Math. Comp., 33:171–184, 1979.
Pai79b
C. C. Paige. Fast numerically
stable computations for generalized linear least squares problems. SIAM J. Numer. Anal., 16:
165–171, 1979.
Pai80
C. C. Paige. Accuracy and effectiveness of the Lanczos algorithm for the symmetric eigenproblem. Linear Algebra Appl.,
34:235–258, 1980.
Pai81
C. C. Paige.
Properties of
numerical algorithms related to
computing controllability. IEEE
Trans. Automat. Control, AC-26:
130–138, 1981.

Golub and Van Loan: gvl.bib

68

Par68

Pai84
[Pai84]

C. C. Paige. A note on a result
of Sun J.-Guang: Sensitivity of
the CS and GSV decompositions.
SIAM J. Numer. Anal., 21:186–
191, 1984.
Pai85

[Pai85]

[Par71]

[Par74a]

C. C. Paige. Computing the
generalized singular value decomposition. SIAM J. Sci. Statist.
Comput., 7:1126–1146, 1986.

V. Pan. How can we speed up matrix multiplication? SIAM Rev.,
26:393–416, 1984.

[Par74b]

B. N. Parlett. Convergence of the
QR algorithm. Numer. Math., [Par76]
7:187–193, 1965. Correction in
Numerische Mathematik 10, pp.
163–164.
Par66

[Par66]

B. N. Parlett. Singular and in- [Par80a]
variant matrices under the QR algorithm. Math. Comp., 20:611–
615, 1966.
Par67

[Par67]

B. N. Parlett.
Computation
of functions of triangular matrices. Memorandum ERL-M481,
Electronics Research Laboratory,
College of Engineering, University of California, Berkeley,
Berkeley, CA, USA, 1974.
Par74b

Par65
[Par65]

B. N. Parlett. Analysis of algorithms for reflections in bisectors.
SIAM Rev., 13:197–208, 1971.
Par74a

Pan84
[Pan84]

B. N. Parlett. Global convergence of the basic QR algorithm
on Hessenberg matrices. Math.
Comp., 22:803–817, 1968.
Par71

C. C. Paige. The general linear
model and the generalized singular value decomposition. Linear
Algebra Appl., 70:269–284, 1985.
Pai86

[Pai86]

[Par68]

B. N. Parlett. Canonical decomposition of Hessenberg matrices. [Par80b]
Math. Comp., 21:223–227, 1967.

B. N. Parlett. The Rayleigh quotient iteration and some generalizations for nonnormal matrices.
Math. Comp., 28:679–693, 1974.
Par76
B. N. Parlett.
A recurrence
among the elements of functions
of triangular matrices. Linear Algebra Appl., 14:117–121, 1976.
Par80a
B. N. Parlett. A new look at
the Lanczos algorithm for solving symmetric systems and linear
equations. Linear Algebra Appl.,
29:323–346, 1980.
Par80b
B. N. Parlett. The Symmetric
Eigenvalue Problem. Prentice-

Golub and Van Loan: gvl.bib

69

Hall, Englewood Cliffs, NJ, USA,
1980.
PaiD86
[PD86]

Ple74
[Ple74]

C. C. Paige and P. Van Dooren.
On the quadratic convergence
of Kogbetliantz’s algorithm for
computing the singular value decomposition.
Linear Algebra [Ple86]
Appl., 77:301–313, 1986.
Pea01

[Pea01]

K. Pearson. On lines and planes
of closest fit to points in space.
Philos. Mag., 2:559–572, 1901.

Ple86
R. J. Plemmons.
A parallel
block iterative scheme applied to
computations in structural analysis. SIAM J. Algebraic Discrete
Methods, 7:337–347, 1986.
ParNO85

[PNO85]

Phi71
[Phi71]

R. J. Plemmons. Linear least
squares by elimination and MGS.
J. Assoc. Comput. Mach., 21:
581–585, 1974.

J. L. Phillips. The triangular decomposition of Hankel matrices.
Math. Comp., 25:599–602, 1971.

B. N. Parlett and B. NourOmid. The use of a refined error bound when updating eigenvalues of tridiagonals. Linear Algebra Appl., 68:179–220, 1985.
PooO87

PatJ84
[PO87]
[PJ84]

N. Patel and H. Jordan. A parallelized point rowwise successive
over-relaxation method on a multiprocessor. Parallel Comput., 1:
207–222, 1984.
PotJV87

[PJV87]

ParP73
[PP73]

A. Pothen, S. Jha, and U. Vemapulati.
Orthogonal factorization on a distributed memory multiprocessor. In M. T.
Heath, editor, Hypercube Mul- [PR68]
tiprocessors. SIAM Publications,
Philadelphia, PA, USA, 1987.
PaiL81

[PL81]

E. L. Poole and J. M. Ortega.
Multicolor ICCG methods for
vector computers. SIAM J. Numer. Anal., 24:1394–1418, 1987.

C. C. Paige and C. Van Loan. A
Schur decomposition for Hamiltonian matrices. Linear Algebra [PR69]
Appl., 41:11–32, 1981.

B. N. Parlett and W. G. Poole. A
geometric theory for the QR, LU,
and power iterations. SIAM J.
Numer. Anal., 10:389–412, 1973.
PowR68
M. J. D. Powell and J. K.
Reid. On applying Householder’s
method to linear least squares
problems. In Proceedings IFIP
Congress, pages 122–126, 1968.
ParR69
B. N. Parlett and C. Reinsch.
Balancing a matrix for calcula-

Golub and Van Loan: gvl.bib

70

tion of eigenvalues and eigenvectors. Numer. Math., 13:292–304,
1969. Also in [WR71, pages 315– [PS78]
326].
ParR70
[PR70]

B. N. Parlett and J. K. Reid. On
the solution of a system of linear
equations whose matrix is symmetric but not definite. BIT, 10:
386–397, 1970.
ParR81

[PR81]

B. N. Parlett and J. K. Reid.
Tracking the progress of the
Lanczos algorithm for large symmetric eigenproblems. IMA J.
Numer. Anal., 1:135–155, 1981.

J. D. Pryce.
A new measure of relative error for vectors.
SIAM J. Numer. Anal., 21:202–
221, 1984.

[PS79]

[PS81]

[PS73]

[PS82a]

[PS75]

C. C. Paige and M. A. Saunders.
Solution of sparse indefinite systems of linear equations. SIAM J.
Numer. Anal., 12:617–629, 1975.

C. C. Paige and M. A. Saunders.
Algorithm 583 LSQR: Sparse linear equations and least squares
problems. ACM Trans. Math.
Software, 8:195–209, 1982.
PaiS82b

[PS82b]

M. S. Paterson and L. J. Stockmeyer. On the number of nonscalar multiplications necessary
to evaluate polynomials. SIAM
J. Comput., 2:60–66, 1973.
PaiS75

C. C. Paige and M. Saunders.
Towards a generalized singular
value decomposition. SIAM J.
Numer. Anal., 18:398–405, 1981.
PaiS82a

J. D. Pryce. Multiplicative error analysis of matrix transformation algorithms. IMA J. Numer. Anal., 5:437–445, 1985.
PatS73

B. N. Parlett and D. S. Scott.
The Lanczos algorithm with selective orthogonalization. Math.
Comp., 33:217–238, 1979.
PaiS81

Pry85
[Pry85]

C. C. Paige and M. A. Saunders. A bidiagonalization algorithm for sparse linear equations
and least squares problems. Technical Report SOL 78-19, Operations Research, Stanford University, Stanford, CA, USA, 1978.
ParS79

Pry84
[Pry84]

PaiS78

C. C. Paige and M. A. Saunders.
LSQR: An algorithm for sparse
linear equations and sparse least
squares. ACM Trans. Math. Software, 8:43–71, 1982.
ParSS82

[PSS82]

B. N. Parlett, H. Simon, and
L. M. Stringer. On estimating the
largest eigenvalue with the Lanczos algorithm. Math. Comp., 38:
153–166, 1982.

Golub and Van Loan: gvl.bib

71

Rat82

PopT57
[PT57]

D. A. Pope and C. Tompkins. [Rat82]
Maximizing functions of rotations: Experiments concerning
speed of diagonalization of symmetric matrices using Jacobi’s
method.
J. Assoc. Comput.
[RB68]
Mach., 4:459–466, 1957.
PetW69

[PW69]

G. Peters and J. H. Wilkinson.
Eigenvalue of Ax = λBx with
band symmetric A and B. Comput. J., 12:398–404, 1969.

W. Rath. Fast Givens rotations
for orthogonal similarity. Numer.
Math., 40:47–56, 1982.
ReiB68
C. Reinsch and F. L. Bauer. Rational QR transformations with
Newton’s shift for symmetric
tridiagonal matrices.
Numer.
Math., 11:264–272, 1968. Also in
[WR71, pages 257–265].
Rei67

PetW70a
[PW70a]

G. Peters and J. H. Wilkinson.
Ax = λBx and the generalized
eigenproblem. SIAM J. Numer.
Anal., 7:479–492, 1970.

[Rei67]

PetW70b
[PW70b]

Rei71a

G. Peters and J. H. Wilkinson.
The least squares problem and [Rei71a]
pseudo-inverses. Comput. J., 13:
309–316, 1970.
PetW71

[PW71]

[PW79]

G. Peters and J. H. Wilkinson.
Inverse iteration, ill-conditioned
equations, and Newton’s method.
SIAM Rev., 21:339–360, 1979.

J. K. Reid. A note on the stability
of Gaussian elimination. J. Inst.
Math. Appl., 8:374–375, 1971.
Rei71b

G. Peters and J. H. Wilkinson. [Rei71b]
The calculation of specified eigenvectors by inverse iteration. In
J. H. Wilkinson and C. Reinsch,
editors, Handbook for Automatic
Computation Vol. 2: Linear Algebra, pages 418–439. SpringerVerlag, New York, NY, USA,
1971.
PetW79

J. K. Reid. A note on the least
squares solution of a band system of linear equations by Householder reductions. Comput. J.,
10:188–189, 1967.

[Rei72]

J. K. Reid. On the method of
conjugate gradients for the solution of large sparse linear equations. In J. K. Reid, editor, Large
Sparse Sets of Linear Equations,
pages 231–254. Academic Press,
New York, NY, USA, 1971.
Rei72
J. K. Reid. The use of conjugate gradients for systems of
linear equations possessing property A. SIAM J. Numer. Anal.,
9:325–332, 1972.

Golub and Van Loan: gvl.bib

72

Rod73

Ric66b
[Ric66a]

J. R. Rice.
Experiments on
Gram-Schmidt
orthogonalization. Math. Comp., 20:325–328,
1966.

[Rod73]

Ric66a
[Ric66b]

Rod82a

J. R. Rice. A theory of condition. SIAM J. Numer. Anal., 3: [Rod82a]
287–310, 1966.
Ric81

[Ric81]

J. R. Rice. Matrix Computations and Mathematical Software. [Rod82b]
Academic Press, New York, NY,
USA, 1981.
Rin55

[Rin55]

R. F. Rinehart. The equivalence
of definitions of a matrix func- [Ros69]
tion. Amer. Math. Monthly, 62:
395–414, 1955.

J. Rissanen. Algorithms for triangular decomposition of block
Hankel and Toeplitz matrices
with application to factoring positive matrix polynomials. Math.
Comp., 27:147–154, 1973.

C. H. Romine and J. M. Ortega. Parallel solution of triangular systems of equations. Parallel
Comput., 6:109–114, 1988.

[Ruh67]

G. Roderigue, editor. Parallel
Computations. Academic Press,
New York, NY, USA, 1982.

D. J. Rose. An algorithm for
solving a special class of tridiagonal systems of linear equations.
Comm. ACM, 12:234–236, 1969.

A. Ruhe. On the quadratic convergence of the Jacobi method for
normal matrices. BIT, 7:305–313,
1967.
Ruh68

[Ruh68]

Rob77
[Rob77]

Rod82b

Ruh67

RomO88
[RO88]

G. Roderigue, editor. Parallel
Computations. Academic Press,
New York, NY, USA, 1982.

Ros69

Ris73
[Ris73]

G. Rodrigue. A gradient method
for the matrix eigenvalue problem
Ax = λBx. Numer. Math., 22:1–
16, 1973.

H. H. Robertson. The accuracy of [Ruh69a]
error estimates for systems of linear algebraic equations. J. Inst.
Math. Appl., 20:409–414, 1977.

A. Ruhe. On the quadratic convergence of a generalization of the
Jacobi method to arbitrary matrices. BIT, 8:210–231, 1968.
Ruh69a
A. Ruhe.
An algorithm for
numerical determination of the
structure of a general matrix.
BIT, 10:196–216, 1969.

Golub and Van Loan: gvl.bib

73

Ruh69b
[Ruh69b]

Ruh83

A. Ruhe. The norm of a matrix [Ruh83]
after a similarity transformation.
BIT, 9:53–58, 1969.
Ruh70a

[Ruh70a]

A. Ruhe. Perturbation bounds
for means of eigenvalues and in- [Ruh87]
variant subspaces. BIT, 10:343–
354, 1970.
Ruh70b

[Ruh70b]

[Rut58]

A. Ruhe. Properties of a matrix
with a very ill-conditioned eigenproblem. Numer. Math., 15:57–
60, 1970.

A. Ruhe. Numerical aspects of
Gram-Schmidt orthogonalization
of vectors. Linear Algebra Appl.,
52/53:591–602, 1983.
Ruh87
A. Ruhe. Closest normal matrix
found! BIT, 27:585–598, 1987.
Rut58
H. Rutishauser. Solution of eigenvalue problems with the WR
transformation. In Applied Mathematics Series, volume 49, pages
47–81. National Bureau of Standards, 1958.

Ruh74
Rut66
[Ruh74]

A. Ruhe.
SOR methods for
the eigenvalue problem with large
sparse matrices. Math. Comp.,
28:695–710, 1974.

[Rut66]

H. Rutishauser.
The Jacobi
method for real symmetric matrices. Numer. Math., 9:1–10, 1966.
Also in [WR71, pages 202–211].

Ruh75
Rut69
[Ruh75]

A. Ruhe.
On the closeness
of eigenvalues and singular val- [Rut69]
ues for almost normal matrices.
Linear Algebra Appl., 11:87–94,
1975.
Ruh78

[Ruh78]

A. Ruhe. A note on the efficient
solution of matrix pencil systems.
BIT, 18:276–281, 1978.

Rut70
[Rut70]

Ruh79
[Ruh79]

A. Ruhe. Implementation aspects of band Lanczos algorithms
for computation of eigenvalues of
large sparse symmetric matrices.
Math. Comp., 33:680–687, 1979.

H. Rutishauser. Computation aspects of F.L. Bauer’s simultaneous iteration method. Numer.
Math., 13:4–13, 1969.

H. Rutishauser. Simultaneous
iteration method for symmetric
matrices. Numer. Math., 16:205–
223, 1970. Also in [WR71, pages
284–302].
RosW72a

[RW72a]

D. J. Rose and R. A. Willoughby,
editors.
Sparse Matrices and
Their Applications.
Plenum

Golub and Van Loan: gvl.bib

74

solving indefinite and nonsymmetric linear systems. SIAM J.
Sci. Statist. Comput., 5:203–228,
1984.

Press, New York, NY, USA,
1972.
RuhW72b
[RW72b]

A. Ruhe and T. Wiberg. The
method of conjugate gradients
used in inverse iteration. BIT, 12: [Saa86]
543–554, 1972.
RodW84a

[RW84a]

G. Roderigue and D. Wolitzer.
Preconditioning by incomplete
block cyclic reduction. Math.
Comp., 42:549–566, 1984.
[Saa87]
RodW84b

[RW84b]

G. Roderigue and D. Wolitzer.
Preconditioning by incomplete
block cyclic reduction. Math.
Comp., 42:549–566, 1984.
[Sam71]
Saa80

[Saa80]

Y. Saad. On the rates of convergence of the Lanczos and the
block Lanczos methods. SIAM J.
Numer. Anal., 17:687–706, 1980.

[SB79]

Y. Saad. Krylov subspace methods for solving large unsymmetric
linear systems. Math. Comp., 37:
[SBI+ 70]
105–126, 1981.
Saa82

[Saa82]

Y. Saad. The Lanczos biorthogonalization algorithm and other
oblique projection methods for
solving large unsymmetric systems. SIAM J. Numer. Anal., 19:
485–506, 1982.
[Sch09]
Saa84

[Saa84]

Y. Saad. Practical use of some
Krylov subspace methods for

Y. Saad. On the condition number of some Gram matrices arising from least squares approximation in the complex plane. Numer. Math., 48:337–348, 1986.
Saa87
Y. Saad. On the Lanczos method
for solving symmetric systems
with several right hand sides.
Math. Comp., 48:651–662, 1987.
Sam71
A. Sameh. On Jacobi and Jacobilike algorithms for a parallel computer. Math. Comp., 25:579–590,
1971.
SerB79

Saa81
[Saa81]

Saa86

S. Serbin and S. Blalock. An algorithm for computing the matrix cosine. SIAM J. Sci. Statist.
Comput., 1:198–204, 1979.
SmiBI+70
B. T. Smith, J. M. Boyle,
Y. Ikebe, V. C. Klema, and
C. B. Moler. Matrix Eigensystem Routines: EISPACK Guide.
Springer-Verlag, New York, NY,
USA, second edition, 1970.
Sch09
I. Schur. On the characteristic
roots of a linear substitution with
an application to the theory of integral equations. Math. Ann., 66:
488–510, 1909. German.

Golub and Van Loan: gvl.bib

75

Sco78

Sch64
[Sch64]

A. Schonage. On the quadratic [Sco78]
convergence of the Jacobi process. Numer. Math., 6:410–412,
1964.
Sch66

[Sch66]

P. Schoenemann. A generalized
solution of the orthogonal Procrustes problem. Psychometrika, [Sco79a]
31:1–10, 1966.
Sch68

[Sch68]

H. R. Schwartz. Tridiagonalization of a symmetric band matrix.
Numer. Math., 12:231–241, 1968.
Also in [WR71, pages 273–283].
Sch74

[Sch74]

[Sch79]

[Sco79b]

[Sco84]

A. Schonage. Arbitrary perturbations of Hermitian matrices. Linear Algebra Appl., 24:143–149,
1979.

R. Schreiber.
Solving eigenvalue and singular value problems on an undersized systolic array. SIAM J. Sci. Statist. Comput., 7:441–451, 1986.

D. S. Scott.
How to make
the Lanczos algorithm converge
slowly. Math. Comp., 33:239–247,
1979.

D. S. Scott. Computing a few
eigenvalues and eigenvectors of a
symmetric band matrix. SIAM J.
Sci. Statist. Comput., 5:658–666,
1984.
Sco85

[Sco85]

Sch87
[Sch87]

D. S. Scott.
Block Lanczos
software for symmetric eigenvalue problems. Technical Report ORNL/CSD-48, Oak Ridge
National Laboratory, Oak Ridge,
TN, USA, 1979.

Sco84

Sch86
[Sch86]

Sco79a

Sco79b

H. R. Schwartz. The method
of coordinate relaxation for (A −
λB)x = 0. Numer. Math., 23:
135–152, 1974.
Sch79

D. S. Scott. Analysis of the symmetric Lanczos process. Technical Report M78/40, UCB-ERL,
University of California, Berkeley, Berkeley, CA, USA, 1978.

W. Schönauer. Scientific Com- [Sea69]
puting on Vector Computers.
North-Holland, Amsterdam, The
Netherlands, 1987.

D. S. Scott. On the accuracy
of the Gershgorin circle theorem
for bounding the spread of a real
symmetric matrix. Linear Algebra Appl., 65:147–155, 1985.
Sea69
J. J. Seaton. Diagonalization of
complex symmetric matrices using a modified Jacobi method.
Comput. J., 12:156–157, 1969.

Golub and Van Loan: gvl.bib

76

Ske80

Sea86
[Sea86]

M. K. Seager. Parallelizing conjugate gradient for the Cray X-MP.
Parallel Comput., 3:35–47, 1986.

[Ske80]

Ser80
[Ser80]

S. Serbin. On factoring a class
of complex symmetric matrices [Ske81]
without pivoting. Math. Comp.,
35:1231–1234, 1980.
She55

[She55]

J. W. Sheldon. On the numerical solution of elliptic difference [SL89]
equations. Math. Tables Aids
Comput., 9:101–112, 1955.
ScoHW86

[SHW86]

D. S. Scott, M. T. Heath, and
R. C. Ward. Parallel block Jacobi eigenvalue algorithms using
[SLN75]
systolic arrays. Linear Algebra
Appl., 77:345–356, 1986.
Sim84

[Sim84]

H. Simon.
Analysis of the
symmetric Lanczos algorithm
[Smi67]
with reorthogonalization methods. Linear Algebra Appl., 61:
101–132, 1984.
SamK78

[SK78]

A. Sameh and D. Kuck. On stable
parallel linear system solvers. J. [Smi70]
Assoc. Comput. Mach., 25:81–91,
1978.
Ske79

[Ske79]

R. D. Skeel. Scaling for numeri- [Sor85]
cal stability in Gaussian elimination. J. Assoc. Comput. Mach.,
26:494–526, 1979.

R. D. Skeel. Iterative refinement implies numerical stability
for Gaussian elimination. Math.
Comp., 35:817–832, 1980.
Ske81
R. D. Skeel. Effect of equilibration on residual size for partial
pivoting. SIAM J. Numer. Anal.,
18:449–455, 1981.
SchL89
R. Schreiber and C. Van Loan. A
storage efficient WY representation for products of Householder
transformations. SIAM J. Sci.
Statist. Comput., 10:53–57, 1989.
SamLN75
A. Sameh, J. Lermit, and K. Noh.
On the intermediate eigenvalues of symmetric sparse matrices.
BIT, 12:543–554, 1975.
Smi67
R. A. Smith.
The condition
numbers of the matrix eigenvalue
problem. Numer. Math., 10:232–
240, 1967.
Smi70
F. Smithies.
Integral Equations.
Cambridge University
Press, Cambridge, UK, 1970.
Sor85
D. Sorensen. Analysis of pairwise
pivoting in Gaussian elimination.
IEEE Trans. Comput., C-34:274–
278, 1985.

Golub and Van Loan: gvl.bib

77

SaaS86

SchP87
[SP87]

R. Schreiber and B. N. Parlett. Block reflectors: Theory and
computation. SIAM J. Numer.
Anal., 25:189–205, 1987.

[SS86]

SwaS73
[SS73]

P. N. Swarztrauber and R. A.
Sweet. The direct solution of
the discrete Poisson equation on [SS87]
a disk. SIAM J. Numer. Anal.,
10:900–907, 1973.
SinS76

[SS76]

B. Singer and S. Spilerman. The
representation of social processes
by Markov models. Amer. J. Sociology, 82:1–54, 1976.
[ST86]
SchS79

[SS79]

K. Schittkowski and J. Stoer. A
factorization method for the solution of constrained linear least
squares problems allowing for [Ste69]
subsequent data changes. Numer.
Math., 31:431–463, 1979.
SaaS85a

[SS85a]

Y. Saad and M. H. Schultz.
Data communication in hypercubes. Technical Report YALEU [Ste70]
DCS RR-428, Computer Science,
Yale University, New Haven, CT,
USA, 1985.
SaaS85b

[SS85b]

Y. Saad and M. H. Schultz.
Topological properties of hyper- [Ste71]
cubes. Technical Report YALEU
DCS RR-389, Computer Science,
Yale University, New Haven, CT,
USA, 1985.

Y. Saad and M. Schultz. GMRES: A generalized minimal
residual algorithm for solving
nonsymmetric linear systems.
SIAM J. Sci. Statist. Comput.,
7:856–869, 1986.
ShrS87
G. Shroff and R. Schreiber. Convergence of block Jacobi methods.
Technical Report 87-25,
Computer Science, Rensselaer
Polytechnic Institute, Troy, NY,
USA, 1987.
SchT86
R. Schreiber and W. P. Tang. On
systolic arrays for updating the
Cholesky factorization. BIT, 26:
451–466, 1986.
Ste69
G. W. Stewart.
Accelerating
the orthogonal iteration for the
eigenvectors of a Hermitian matrix. Numer. Math., 13:362–376,
1969.
Ste70
G. W. Stewart. Incorporating origin shifts into the QR algorithm
for symmetric tridiagonal matrices. Comm. ACM, 13:365–367,
1970.
Ste71
G. W. Stewart. Error bounds
for approximate invariant subspaces of closed linear operators.
SIAM J. Numer. Anal., 8:796–
808, 1971.

Golub and Van Loan: gvl.bib

78

problem Ax = λBx.
Math.
Comp., 29:600–606, 1975.

Ste72
[Ste72]

G. W. Stewart. On the sensitivity
of the eigenvalue problem Ax =
λBx. SIAM J. Numer. Anal., 9:
669–686, 1972.

Ste75c
[Ste75c]

Ste73a
[Ste73a]

G. W. Stewart. Conjugate direction methods for solving systems of linear equations. Numer.
Math., 21:284–297, 1973.

Ste76a

Ste73b
[Ste73b]

G. W. Stewart. Error and perturbation bounds for subspaces associated with certain eigenvalue
problems. SIAM Rev., 15:727–
764, 1973.

[Ste76a]

Ste73c
[Ste73c]

G. W. Stewart.
Introduction
to Matrix Computations. Academic Press, New York, NY,
USA, 1973.

[Ste76b]

G. W. Stewart.
The numerical treatment of large eigenvalue problems. In Proceedings
IFIP Congress 74, pages 666–
672. North-Holland, 1974.
Ste75a

[Ste75a]

[Ste75b]

G. W. Stewart. Gershgorin theory for the generalized eigenvalue

G. W. Stewart. A bibliographical tour of the large sparse generalized eigenvalue problem. In
J. R. Bunch and D. J. Rose,
editors, Sparse Matrix Computations. Academic Press, New
York, NY, USA, 1976.
Ste76c

[Ste76c]

G. W. Stewart. The convergence
of the method of conjugate gradients at isolated extreme points in
the spectrum. Numer. Math., 24:
85–93, 1975.
[Ste76d]
Ste75b

G. W. Stewart. Algorithm 406
HQR3 and EXCHNG: Fortran
subroutines for calculating and
ordering and eigenvalues of a real
upper Hessenberg matrix. ACM
Trans. Math. Software, 2:275–
280, 1976.
Ste76b

Ste74
[Ste74]

G. W. Stewart. Methods of simultaneous iteration for calculating
eigenvectors of matrices. In J. H.
Miller, editor, Topics in Numerical Analysis II, pages 185–196.
Academic Press, New York, NY,
USA, 1975.

G. W. Stewart. The economical
storage of plane rotations. Numer. Math., 25:137–138, 1976.
Ste76d
G. W. Stewart. Simultaneous iteration for computing invariant
subspaces of non-Hermitian matrices. Numer. Math., 25:12–36,
1976.

Golub and Van Loan: gvl.bib

79

Ste77a
[Ste77a]

G. W. Stewart. On the perturbation of pseudo-inverses, projections, and linear least squares
problems. SIAM Rev., 19:634–
662, 1977.

Ste79c
[Ste79c]

Ste80

Ste77b
[Ste77b]

G. W. Stewart. Perturbation [Ste80]
bounds for the QR factorization
of a matrix. SIAM J. Numer.
Anal., 14:509–518, 1977.
Ste77c

[Ste77c]

G. W. Stewart. Sensitivity coefficients for the effects of errors
[Ste81a]
in the independent variables in a
linear regression. Technical Report TR-571, Computer Science,
University of Maryland, College
Park, MD, USA, 1977.
Ste78

[Ste78]

G. W. Stewart. Perturbation
theory for the generalized eigenvalue problem. In C. de Boor
and G. H. Golub, editors, Recent
Advances in Numerical Analysis.
Academic Press, New York, NY,
USA, 1978.

[Ste81b]

[Ste83]

G. W. Stewart. The effects of
rounding error on an algorithm
for downdating a Cholesky factorization. J. Inst. Math. Appl.,
23:203–213, 1979.
Ste79b

[Ste79b]

G. W. Stewart. The efficient
generation of random orthogonal
matrices with an application to
condition estimators. SIAM J.
Numer. Anal., 17:403–409, 1980.
Ste81a
D. Stevenson. A proposed standard for binary floating point
arithmetic. IEEE Computer, 14:
51–62, March 1981.
Ste81b
G. W. Stewart. On the implicit
deflation of nearly singular systems of linear equations. SIAM J.
Sci. Statist. Comput., 2:136–140,
1981.
Ste83

Ste79a
[Ste79a]

G. W. Stewart. Perturbation
bounds for the definite generalized eigenvalue problem. Linear
Algebra Appl., 23:69–86, 1979.

G. W. Stewart.
A note on [Ste84a]
the perturbation of singular values. Linear Algebra Appl., 28:
213–216, 1979.

G. W. Stewart. A method for
computing the generalized singular value decomposition. In
B. Kågström and A. Ruhe, editors, Matrix Pencils, pages 207–
220. Springer-Verlag, New York,
NY, USA, 1983.
Ste84a
G. W. Stewart. On the asymptotic behavior of scaled singular value and QR decompositions.
Math. Comp., 43:483–490, 1984.

Golub and Van Loan: gvl.bib

80

Ste84b
[Ste84b]

Sto75b

G. W. Stewart. On the invariance [Sto75b]
of perturbed null vectors under
column scaling. Numer. Math.,
33,34:61–66, 1984.

H. S. Stone. Parallel tridiagonal equation solvers. ACM Trans.
Math. Software, 1:289–307, 1975.
Str69

Ste84c
[Str69]
[Ste84c]

G. W. Stewart. Rank degeneracy.
SIAM J. Sci. Statist. Comput., 5:
403–413, 1984.

V. Strassen. Gaussian elimination is not optimal.
Numer.
Math., 13:354–356, 1969.
Str88

Ste84d
[Str88]
[Ste84d]

G. W. Stewart. A second order
perturbation expansion for small
singular values. Linear Algebra
Appl., 56:231–236, 1984.

G. Strang. Linear Algebra and
Its Applications. Academic Press,
New York, NY, USA, third edition, 1988.
Sun82

Ste85
[Sun82]
[Ste85]

G. W. Stewart. A Jacobi-like algorithm for computing the Schur
decomposition of a nonhermitian
matrix. SIAM J. Sci. Statist.
Comput., 6:853–862, 1985.
Ste87

[Ste87]

J. Guang Sun. A note on Stewart’s theorem for definite matrix
pairs. Linear Algebra Appl., 48:
331–339, 1982.
Sun83

[Sun83]

G. W. Stewart. Collinearity and
least squares regression. Statist.
Sci., 2:68–100, 1987.

J. Guang Sun. Perturbation analysis for the generalized singular
value problem. SIAM J. Numer.
Anal., 20:611–625, 1983.
SymW80

Sto73
[SW80]
[Sto73]

H. S. Stone. An efficient parallel algorithm for the solution of a
tridiagonal linear system of equations. J. Assoc. Comput. Mach.,
20:27–38, 1973.

H. J. Symm and J. H. Wilkinson.
Realistic error bounds for a simple eigenvalue and its associated
eigenvector. Numer. Math., 35:
113–126, 1980.
Swa79

Sto75a
[Swa79]
[Sto75a]

H. Stone. Parallel tridiagonal
equation solvers. ACM Trans.
Math. Software, 1:289–307, 1975.

P. N. Swarztrauber. A parallel algorithm for solving general tridiagonal equations. Math. Comp.,
33:185–199, 1979.

Golub and Van Loan: gvl.bib

81

Tsa75

Swe74
[Swe74]

R. A. Sweet. A generalized cyclic
reduction algorithm. SIAM J.
Numer. Anal., 11:506–520, 1974.

[Tsa75]

Swe77
[Swe77]

R. A. Sweet. A cyclic reduction
algorithm for solving block tridi[TW70]
agonal systems of arbitrary dimension. SIAM J. Numer. Anal.,
14:706–720, 1977.
TurA61

[TA61]

W. P. Tang and G. H. Golub. The
block decomposition of a Vandermonde matrix and its applica- [Uhl73]
tions. BIT, 21:505–517, 1981.
Tre64

[Tre64]

W. F. Trench. An algorithm for
the inversion of finite Toeplitz
matrices. J. SIAM, 12:515–522,
1964.

[Uhl76]

W. F. Trench.
Inversion of
Toeplitz band matrices. Math.
Comp., 28:1089–1095, 1974.
TreS87

[TS87]

L. N. Trefethen and R. S.
Schreiber. Average case stability
of Gaussian elimination. Technical Report 88-3, Numerical Analysis, Department of Mathematics, MIT, MA, 1987.

G. L. Thompson and R. L. Weil.
Reducing the rank of A − λB.
Proc. Amer. Math. Soc., 26:548–
554, 1970.

G. L. Thompson and R. L. Weil.
Roots of matrix pencils Ay =
λBy: Existence, calculations,
and relations to game theory.
Linear Algebra Appl., 5:207–226,
1972.
Uhl73
F. Uhlig. Simultaneous block diagonalization of two real symmetric matrices. Linear Algebra
Appl., 7:281–289, 1973.
Uhl76

Tre74
[Tre74]

ThoW70

ThoW72

H. W. Turnbull and A. C. Aitken.
An Introduction to the Theory of [TW72]
Canonical Matrices. Dover Publications, New York, NY, USA,
1961.
TanG81

[TG81]

N. K. Tsao. A note on implementing the Householder transformation.
SIAM J. Numer.
Anal., 12:53–58, 1975.

F. Uhlig. A canonical form for
a pair of real symmetric matrices
that generate a nonsingular pencil. Linear Algebra Appl., 14:189–
210, 1976.
Und75

[Und75]

R. Underwood.
An iterative
block Lanczos method for the solution of large sparse symmetric
eigenproblems. Technical Report
STAN-CS-75-496, Computer Science, Stanford University, Stanford, CA, USA, 1975.

Golub and Van Loan: gvl.bib

82

Var72

Van71
[Van71]

J. Vandergraft.
Generalized [Var72]
Rayleigh methods with applications to finding eigenvalues of
large matrices. Linear Algebra
Appl., 4:353–368, 1971.
Var61

[Var61]

Var73

R. S. Varga. On higher-order
[Var73]
stable implicit methods for solving parabolic partial differential
equations. J. Math. Phys., 40:
220–231, 1961.
Var62

[Var62]

R. S. Varga. Matrix Iterative
Analysis. Prentice-Hall, Englewood Cliffs, NJ, USA, 1962.

[Var75]

J. M. Varah. The calculation of
the eigenvectors of a general complex matrix by inverse iteration. [Var76]
Math. Comp., 22:785–791, 1968.
Var68b

[Var68b]

J. M. Varah. Rigorous machine
bounds for the eigensystem of a
general complex matrix. Math. [Var79]
Comp., 22:793–801, 1968.
Var70a

[Var70a]

J. M. Varah. Computing invariant subspaces of a general matrix
when the eigensystem is poorly [vdS69]
determined. Math. Comp., 24:
137–149, 1970.

R. S. Varga. Minimal Gershgorin sets for partitioned matrices. SIAM J. Numer. Anal., 7:
493–507, 1970.

J. M. Varah. A lower bound for
the smallest singular value of a
matrix. Linear Algebra Appl., 11:
1–2, 1975.
Var76
R. S. Varga. On diagonal dominance arguments for bounding
kA−1 k. Linear Algebra Appl., 14:
211–217, 1976.
Var79
J. M. Varah. On the separation
of two matrices. SIAM J. Numer.
Anal., 16:216–222, 1979.
vdS69
A. van der Sluis. Condition numbers and equilibration matrices.
Numer. Math., 14:14–23, 1969.
vdS70

Var70b
[Var70b]

J. M. Varah. On the numerical
solution of ill-conditioned linear
systems with applications to illposed problems. SIAM J. Numer. Anal., 10:257–267, 1973.
Var75

Var68a
[Var68a]

J. M. Varah. On the solution
of block-tridiagonal systems arising from certain finite-difference
equations. Math. Comp., 26:859–
868, 1972.

[vdS70]

A. van der Sluis. Condition,
equilibration, and pivoting in linear algebraic systems. Numer.
Math., 15:74–86, 1970.

Golub and Van Loan: gvl.bib

83

WalAC+88

vdS75a
[vdS75a]

A. van der Sluis. Perturbations [WAC+ 88]
of eigenvalues of nonnormal matrices. Comm. ACM, 18:30–36,
1975.
vdS75b

[vdS75b]

A. van der Sluis. Stability of the
solutions of linear least squares
problem. Numer. Math., 23:241–
254, 1975.
vdSV86

[vdSdV86]

A. van der Sluis and H. A. Van
der Vorst. The rate of convergence of conjugate gradients. Numer. Math., 48:543–560, 1986.

Wal88
[Wal88]

vdSV79
[vdSV79]

A. van der Sluis and G. W.
Veltkamp. Restoring rank and
consistency by orthogonal projec- [War75]
tion. Linear Algebra Appl., 28:
257–278, 1979.
Vet75

[Vet75]

W. J. Vetter. Vector structures [War77]
and solutions of linear matrix
equations. Linear Algebra Appl.,
10:181–188, 1975.
vK66

[vK66]

H. P. M. van Kempen.
On [War81]
quadratic convergence of the special cyclic Jacobi method. Numer. Math., 9:19–22, 1966.
Wac66

[Wac66]

D. W. Walker, T. Aldcroft,
A. Cisneros, G. Fox, and W. Furmanski. LU decomposition of
banded matrices and the solution of linear systems on hypercubes. In G. Fox, editor, The
Third Conference on Hypercube
Concurrent Computers and Applications, Vol. II, Applications,
pages 1635–1655. ACM Press,
New York, NY, USA, 1988.

E. L. Wachpress. Iterative Solu- [Wat73]
tion of Elliptic Systems. PrenticeHall, Englewood Cliffs, NJ, USA,
1966.

H. F. Walker.
Implementation of the GMRES method using Householder transformations.
SIAM J. Sci. Statist. Comput., 9:
152–163, 1988.
War75
R. C. Ward. The combination
shift QZ algorithm. SIAM J. Numer. Anal., 12:835–853, 1975.
War77
R. C. Ward. Numerical computation of the matrix exponential
with accuracy estimate. SIAM J.
Numer. Anal., 14:600–614, 1977.
War81
R. C. Ward. Balancing the generalized eigenvalue problem. SIAM
J. Sci. Statist. Comput., 2:141–
152, 1981.
Wat73
G. A. Watson. An algorithm for
the inversion of block matrices of
Toeplitz form. J. Assoc. Comput.
Mach., 20:409–415, 1973.

Golub and Van Loan: gvl.bib

84

Wil61

Wat82
[Wat82]

D. S. Watkins. Understanding [Wil61]
the QR algorithm. SIAM Rev.,
24:427–440, 1982.
Wat88

J. H. Wilkinson. Error analysis of
direct methods of matrix inversion. J. Assoc. Comput. Mach.,
10:281–330, 1961.
Wil63

[Wat88]

G. A. Watson. The smallest perturbation of a submatrix which
lowers the rank of the matrix.
IMA J. Numer. Anal., 8:295–304,
1988.

[Wil63]

Wil65a

Wed72
[Wed72]

P.Å. Wedin.
Perturbation [Wil65a]
bounds in connection with the
singular value decomposition.
BIT, 12:99–111, 1972.
Wed73a

[Wed73a]

[Wil65b]

P.Å. Wedin. On the almost rankdeficient case of the least squares
problem. BIT, 13:344–354, 1973.
[Wil68a]
P.Å. Wedin. Perturbation theory
for pseudo-inverses. BIT, 13:217–
232, 1973.
WarG78

[WG78]

J. H. Wilkinson. The Algebraic
Eigenvalue Problem. Claredon
Press, Oxford, UK, 1965.
Wil65b
J. H. Wilkinson. Convergence
of the LR, QR, and related algorithms. Comput. J., 8:77–84,
1965.
Wil68a

Wed73b
[Wed73b]

J. H. Wilkinson. Rounding Errors
in Algebraic Processes. PrenticeHall, Englewood Cliffs, NJ, USA,
1963.

J. H. Wilkinson. Almost diagonal matrices with multiple or
close eigenvalues. Linear Algebra
Appl., 1:1–12, 1968.
Wil68c

R. C. Ward and L. J. Gray. [Wil68b]
Eigensystem computation for
skew-symmetric and a class of
symmetric matrices. ACM Trans.
Math. Software, 4:278–285, 1978.

J. H. Wilkinson. Global convergence of tridiagonal QR algorithm with origin shifts. Linear
Algebra Appl., 1:409–420, 1968.
Wil68b

Wid78
[Wil68c]
[Wid78]

O. Widlund. A Lanczos method
for a class of nonsymmetric systems of linear equations. SIAM J.
Numer. Anal., 15:801–812, 1978.

J. H. Wilkinson. A priori error analysis of algebraic processes. In Proceedings International Congress Math. (Moscow:
Izdat. Mir), pages 629–639, 1968.

Golub and Van Loan: gvl.bib

85

Wil71
[Wil71]

Win68

J. H. Wilkinson. Modern error [Win68]
analysis. SIAM Rev., 14:548–568,
1971.

Woz80

Wil72
[Wil72]

J. H. Wilkinson. Note on matrices with a very ill-conditioned
eigenproblem. Numer. Math., 19:
176–178, 1972.

[Woz80]

[WR71]
J. H. Wilkinson. Some recent
advances in numerical linear algebra. In D. A. H. Jacobs, editor, The State of the Art in
Numerical Analysis, pages 1–53.
Academic Press, New York, NY,
USA, 1977.
[Wra73]
Wil78

[Wil78]

J. H. Wilkinson. Linear differential equations and Kronecker’s
canonical form. In C. de Boor
and G. H. Golub, editors, Recent [Wra75]
Advances in Numerical Analysis,
pages 231–265. Academic Press,
New York, NY, USA, 1978.

J. H. Wilkinson. Kronecker’s
canonical form and the QZ algorithm. Linear Algebra Appl., 28:
285–303, 1979.

J. H. Wilkinson and C. Reinsch,
editors. Linear Algebra, volume 2
of Handbook for Automatic Computation. Springer-Verlag, New
York, NY, USA, 1971.
Wra73
A. Wragg. Computation of the
exponential of a matrix I: Theoretical considerations. J. Inst.
Math. Appl., 11:369–375, 1973.
Wra75
A. Wragg. Computation of the
exponential of a matrix II: Practical considerations.
J. Inst.
Math. Appl., 15:273–278, 1975.
WimZ72

Wil79
[Wil79]

H. Wozniakowski. Roundoff error
analysis of a new class of conjugate gradient algorithms. Linear
Algebra Appl., 29:507–529, 1980.
WilR71

Wil77
[Wil77]

S. Winograd. A new algorithm
for inner product. IEEE Trans.
Comput., C-17:693–694, 1968.

[WZ72]

H. Wimmer and A. D. Ziebur.
Solving
the matrix equation
P
fp (A)Xgp (A). SIAM Rev., 14:
318–323, 1972.
YouJ80

Wil84
[YJ80]
[Wil84]

J. H. Wilkinson. On neighboring
matrices with quadratic elementary divisors. Numer. Math., 44:
1–21, 1984.

D. M. Young and K. C. Jea. Generalized conjugate gradient acceleration of nonsymmetrizable iterative methods. Linear Algebra
Appl., 34:159–194, 1980.

Golub and Van Loan: gvl.bib

86

Yoh79
[Yoh79]

J. M. Yohe. Software for interval arithmetic: A reasonable
portable package. ACM Trans.
Math. Software, 5:50–63, 1979.
You70

[You70]

D. M. Young. Convergence properties of the symmetric and unsymmetric over-relaxation methods. Math. Comp., 24:793–807,
1970.
You71

[You71]

D. M. Young. Iterative Solution of Large Linear Systems.
Academic Press, New York, NY,
USA, 1971.
You72

[You72]

D. M. Young. Generalization of
property A and consistent ordering. SIAM J. Numer. Anal., 9:
454–463, 1972.
Zoh69

[Zoh69]

S. Zohar. Toeplitz matrix inversion: The algorithm of W.F.
Trench.
JACM, 16:592–601,
1969.



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