Revised and updated, the third edition of Golub and Van Loan's classic text in computer science provides essential information about the mathematical background and algorithmic skills required for the production of numerical software. This new edition includes thoroughly revised chapters on matrix multiplication problems and parallel matrix computations, expanded treatment of CS decomposition, an updated overview of floating point arithmetic, a more accurate rendition of the modified Gram-Schmidt process, and new material devoted to GMRES, QMR, and other methods designed to handle the sparse unsymmetric linear system problem.
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'Praise for previous editions:' "A wealth of material, some old and classical, some new and still subject to debate. It will be a valuable reference source for workers in numerical linear algebra as well as a challenge to students."--'SIAM Review' "In purely academic terms the reader with an interest in matrix computations will find this book to be a mine of insight and information, and a provocation to thought; the annotated bibliographies are helpful to those wishing to explore further. One could not ask for more, and the book should be considered a resounding success."--'Bulletin of the Institute of Mathematics and its Applications'
About the Author
Gene H. Golub is professor of computer science at Stanford University. Charles F. Van Loan is professor of computer science at Cornell University.
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First Sentence
The proper study of matrix computations begins with the study of the matrix-matrix multiplication problem. Read the first page
Front Cover | Copyright | Table of Contents | Excerpt | Index | Back Cover
The proper study of matrix computations begins with the study of the matrix-matrix multiplication problem. Read the first page
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Front Cover | Copyright | Table of Contents | Excerpt | Index | Back Cover
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Customer Reviews
Most helpful customer reviews
By ZAck
Format:Paperback|Amazon Verified Purchase
My course was suffering before I bought this book. I found it contains every algorithm, and why we use it,but also how we store the data. A great author,a great book
By A Customer
Format:Paperback
This is the book I turn to first when I have to deal with a problem in numerical linear algebra, it's clearly written and has extensive references.
By James Arvo
Format:Paperback
This is one of the definitive texts on computational linear algebra, or more specifically, on matrix computations. The term "matrix computations" is actually the more apt name because the book focuses on computational issues involving matrices,the currency of linear algebra, rather than on linear algebra in the abstract. As an example of this distinction, the authors develop both "saxpy" (scalar "a" times vector "x" plus vector "y") based algorithms and "gaxpy" (generalized saxpy, where "a" is a matrix) based algorithms, which are organized to exploit very efficient low-level matrix computations. This is an important organizing concept that can lead to more efficient matrix algorithms.
For each important algorithm discussed, the authors provide a concise and rigorous mathematical development followed by crystal clear pseudo-code. The pseudo-code has a Pascal-like syntax, but with embedded Matlab abbreviations that make common low-level matrix operations extremely easy to express. The authors also use indentation rather than tedious BEGIN-END notation, another convention that makes the pseudo-code crisp and easy to understand. I have found it quite easy to code up various algorithms from the pseudo-code descriptions given in this book. The authors cover most of the traditional topics such as Gaussian elimination, matrix factorizations (LU, QR, and SVD), eigenvalue problems (symmetric and unsymmetric), iterative methods, Lanczos method, othogonalization and least squares (both constrained and unconstrained), as well as basic linear algebra and error analysis.
I've use this book extensively during the past ten years. It's an invaluable resource for teaching numerical analysis (which invariably includes matrix computations), and for virtually any research that involves computational linear algebra. If you've got matrices, chances are you will appreciate having this book around.
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4.4 out of 5 stars
Most recent customer reviews
4.0 out of 5 stars
from theory to practice.
A few years ago this book permitted me to go reliably from
theoretical linear algebra to practical large-scale numerical
computations, using also LAPACK. Read more
theoretical linear algebra to practical large-scale numerical
computations, using also LAPACK. Read more
Published on Aug 8 2002 by Patrick Van Esch
3.0 out of 5 stars
Still state of the art?
It is now 6 years ago when the last version of this once
superb book was released. Meanwhile, bunches of books
aiming a similiar audience were published. Read more
superb book was released. Meanwhile, bunches of books
aiming a similiar audience were published. Read more
Published on Mar 27 2002
4.0 out of 5 stars
Not an introductory text!
Once you have a grounding in matrix analysis and linear algebra this book makes a good reference. His explanations tend to be terse (even exceptionally so)- more suited for... Read more
Published on Aug 24 2001 by Brian J Hurt
5.0 out of 5 stars
Great Mathematical Text
This book should be placed alongside "Principles of Mathematical Analysis" by Walter Rudin and "Finite Dimensional Vector Spaces" by Paul Halmos as a classic... Read more
Published on Jun 21 2001 by James Sullivan
5.0 out of 5 stars
The Best Reference Text I've Seen on the Subject
When I need to solve a large system of linear equations or better understand an algorithm I am using, this book has proven to be the best place to go. Read more
Published on Nov 24 1999 by Bukkene Bruse
3.0 out of 5 stars
Simple things explained in a too formal way
The book is good, but it could have more useful examples and a less complicated text.
Published on Nov 2 1999 by Marcus
5.0 out of 5 stars
A Bible of Numerical Linear Algebra
Presents an extremely thorough and clear study of one of the most important branches of Applied Mathematics
Published on Oct 26 1999
5.0 out of 5 stars
Excellent book!
Great book on the computational aspects of matrix computations. Has much more detail than NRiC for matrix computations -- of course, NRiC covers more topics. Read more
Published on May 25 1998 by J. D. Morrow
5.0 out of 5 stars
A great reference book for doing numerical analysis.
I recently bought this book and am amazed at how detailed the information is presented. This a great book for anyone doing numerical analysis on the computer. Read more
Published on Jan 11 1998
5.0 out of 5 stars
THE CLASSIC reference for matrix computations!
This book is an invaluable reference for anyone working in matrix computations or linear algebra. I have been using it for years and found it to be clear and comprehensive
Published on Sep 2 1997 by kaplan@vibes.ae.utexas.edu
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