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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 lowlevel 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 pseudocode. The pseudocode has a Pascallike syntax, but with embedded Matlab abbreviations that make common lowlevel matrix operations extremely easy to express. The authors also use indentation rather than tedious BEGINEND notation, another convention that makes the pseudocode crisp and easy to understand. I have found it quite easy to code up various algorithms from the pseudocode 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.
5.0 out of 5 stars
Great Mathematical Text,
By James Sullivan (Chicago IL United States)  See all my reviews
This review is from: Matrix Computations (Paperback)
This book should be placed alongside "Principles of Mathematical Analysis" by Walter Rudin and "Finite Dimensional Vector Spaces" by Paul Halmos as a classic text, one which students/professionals of mathematics will use for years to come. A solid book covering computational matrix theory. I myself used it as a tool to bridge the gap between my formal training in Mathematics and my serious interest in computers. Reader should have some knowledge of basic linear algebra(ie understanding of vector spaces, L2 norms, etc..) before attempting this book. Excercises could be better. A good purchase for those with a more than passing interest.
3.0 out of 5 stars
Still state of the art?,
By A Customer
This review is from: Matrix Computations (Paperback)
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. Some of them, in particular G.W. Stewarts, are nowadays more seasonable. Notably, the "iterative" sections ask for light refreshments. The lack of references to appropriate software routines in these parts is another disadvantage which could be easily overcome in a new edition.
4.0 out of 5 stars
Not an introductory text!,
By Brian J Hurt (Minneapolis, MN United States)  See all my reviews
This review is from: Matrix Computations (Paperback)
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 reminding someone who already knows how the algorithm works or was derived and simply can't remember the details. It lost a star as I've found some annoying typos (for example, in the pseudocode for the GMRES algorithm).
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 from
theoretical linear algebra to practical largescale 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.
5.0 out of 5 stars
Excellent book!,
By Amazon Customer (Albuquerque, NM)  See all my reviews
This review is from: Matrix Computations (Paperback)
Great book on the computational aspects of matrix computations. Has much more detail than NRiC for matrix computations  of course, NRiC covers more topics. One the few places you can actually find out how to code SVD. A steal at $30. Highly recommended!
5.0 out of 5 stars
A great reference book for doing numerical analysis.,
By A Customer
This review is from: Matrix Computations (Paperback)
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. The details on how to work around illconditioned matrices is great.
5.0 out of 5 stars
The Best Reference Text I've Seen on the Subject,
This review is from: Matrix Computations (Paperback)
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. It is broad in scope and the writing is clear.
5.0 out of 5 stars
THE CLASSIC reference for matrix computations!,
By kaplan@vibes.ae.utexas.edu (Austin, Texas)  See all my reviews
This review is from: Matrix Computations (Paperback)
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
5.0 out of 5 stars
Masterpiece, the origin of every matrix computation,
By
Verified Purchase(What's this?)
This review is from: Matrix Computations (Paperback)
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

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Matrix Computations by Charles F. Van Loan (Paperback  Oct. 15 1996)
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