- Paperback: 728 pages
- Publisher: Hopkins Fulfillment Service; 3 edition (Oct 15 1996)
- Language: English
- ISBN-10: 0801854148
- ISBN-13: 978-0801854149
- Product Dimensions: 23.1 x 15.3 x 3.4 cm
- Shipping Weight: 1.4 Kg
- Average Customer Review: 4.5 out of 5 stars See all reviews (12 customer reviews)
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Amazon Bestsellers Rank:
#127,722 in Books (See Top 100 in Books)
- #4 in Books > Science > Mathematics > Matrices
- See Complete Table of Contents
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Product Details |
Product Description
Review
'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'
Book Description
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.
Inside This Book
(Learn More)
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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Concordance
Browse Sample PagesConcordance
Front Cover | Copyright | Table of Contents | Excerpt | Index | Back Cover
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Most helpful customer reviews
5.0 out of 5 stars
One of the best books on the subject,
By A Customer
This review is from: Matrix Computations (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.
5.0 out of 5 stars
Got Matrices?,
By
This review is from: Matrix Computations (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.
4.0 out of 5 stars
from theory to practice.,
By
This review is from: Matrix Computations (Paperback)
A few years ago this book permitted me to go reliably fromtheoretical linear algebra to practical large-scale numerical computations, using also LAPACK. I think this is its place: from the university course level to the practical side. On the other hand, one cannot really say it is as readable as, say, Numerical Recipes: it has a quite terse style.
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