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Numerical Linear Algebra Paperback – 1 Jun 1997

4.5 out of 5 stars 2 customer reviews

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Product details

  • Paperback: 184 pages
  • Publisher: Society for Industrial and Applied Mathematics (1 Jun. 1997)
  • Language: English
  • ISBN-10: 0898713617
  • ISBN-13: 978-0898713619
  • Product Dimensions: 15.2 x 1.9 x 22.8 cm
  • Average Customer Review: 4.5 out of 5 stars  See all reviews (2 customer reviews)
  • Amazon Bestsellers Rank: 388,545 in Books (See Top 100 in Books)
  • See Complete Table of Contents

Product Description


' The authors are to be congratulated on producing a fresh and lively introduction to a fundamental area of numerical analysis.' G. W. Stewart, Mathematics of Computation

'…Each lecture in the textbook is pleasantly written in a conversational style and concludes with a set of related exercises. This low-cost textbook emphasizes many important and relevant topics in numerical linear algebra and seems ideal for a graduate course as long as it is accompanied by a textbook with more mathematical details.' Ricardo D. Fierro, SIAM Review

'Trefethen and Bau clear the dark clouds from numerical problems associated with factoring matrices, solving linear equations, and finding eigenvalues.' P. Cull, CHOICE

'Just exactly what I might have expected - an absorbing look at the familiar topics through the eyes of a master expositor. I have been reading it and learning a lot.' Paul Saylor, University of Illinois, Urbana-Champaign

'A beautifully written textbook offering a distinctive and original treatment. It will be of use to all who teach or study the subject.' Nicholas J. Higham, Professor of Applied Mathematics, University of Manchester

"This is a beautifully written book which carefully brings to the reader the important issues connected with the computational issues in matrix computations. The authors show a broad knowledge of this vital area and make wonderful connections to a variety of problems of current interest. The book is like a delicate soufflé --- tasteful and very light." -Gene Golub, Stanford University.

"I have used Numerical Linear Algebra in my introductory graduate course and I have found it to be almost the perfect text to introduce mathematics graduate students to the subject. I like the choice of topics and the format: a sequence of lectures. Each chapter (or lecture) carefully builds upon the material presented in previous chapters, providing new concepts in a very clear manner. Exercises at the end of each chapter reinforce the concepts, and in some cases introduce new ones. …The emphasis is on the mathematics behind the algorithms, in the understanding of why the algorithms work. …The text is sprinkled with examples and explanations, which keep the student focused." -Daniel B. Szyld, Department of Mathematics, Temple University.

"…This is an ideal book for a graduate course in numerical linear algebra (either in mathematics or in computer science departments); it presents the topics in such a way that background material comes along with the course. …I will use it again next time I teach this course!" -Suely Oliveira, Texas A&M University.

Book Description

This is a concise, insightful introduction to the field of numerical linear algebra. The authors' clear, inviting style and evident love of the field, along with their eloquent presentation of the most fundamental ideas in numerical linear algebra, make it popular with teachers and students alike.

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Top Customer Reviews

Format: Paperback
Rather good book on the computational aspect of linear algebra. To read it its good to have some knowledge in linear algebra but not much is required.
Presents different methods for SVD,QR,LU and eigenvalues decomposition.
Also good chapters about stability etc
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By eddy on 25 Feb. 2013
Format: Paperback Verified Purchase
very easy layout to understand the process of working out. i would recommend to those has very little knowledge of computing or numerical methods
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Most Helpful Customer Reviews on Amazon.com (beta)

Amazon.com: HASH(0x91584900) out of 5 stars 26 reviews
52 of 57 people found the following review helpful
HASH(0x914a2498) out of 5 stars Excellent: the best book I have seen on the subject. 24 Feb. 1999
By JR - Published on Amazon.com
Format: Paperback
This book should be required reading for anyone interested in computational numerics, especially those who are starting in the field. The authors concentrate on the few fundamental topics that underlie and unite the subject. The presentation, while rigorous, is simple, clear and friendly. The authors follow a logical thread and eliminate unnecessary and disorienting aspects that plague other books on the subject. It is easy to pick up the book, read several chapters at a stretch without looking up, and come away with new insights. Unquestionably the most valuable book I have read to date on the subject.
28 of 29 people found the following review helpful
HASH(0x914a24ec) out of 5 stars Excellent...with a few caveats 13 May 2005
By calvinnme - Published on Amazon.com
Format: Paperback
This book on Linear Algebra is excellent. In particular chapters seven through thirty (as far as I have read) are great for self-directed study. However, I found chapters one through six ( through Projectors) a bit terse. Therefore I would highly recommend this book for self-study ONLY IF you already have a good idea of the concept of basic linear algebra including matrix norms, the singular value decomposition, and projectors, and also the correct way to perform a proof...and by a "good idea" I mean you already know how to use these ideas in a practical way. Otherwise, you should only use this book if you have a truly good instructor to guide you through the early material. I started out taking a class using this book four years ago from a poor instructor, and I and the entire class, as far as I could tell from casual conversation, were completely lost. I dropped the class and retook it just recently with an excellent instructor. Her help and insight made a world of difference. It will also help to have a copy of "Matrix Computations" by Golub and Van Loan for reference, especially when you get to the later chapters and eigenproblems.
14 of 14 people found the following review helpful
HASH(0x92687b40) out of 5 stars A must for computational mathematicians 25 Jun. 2002
By Hart Wilson - Published on Amazon.com
Format: Hardcover
The chapters on numerical stability of algorithms and conditioning of numerical problems are excellent. While the focus is of course linear algebra, these principles can be readily extended to all computational mathematics. If you regularly use computational methods and have not yet studied elementary error analysis, this book may revolutionize how you perceive numerical problems.
9 of 9 people found the following review helpful
HASH(0x914a2774) out of 5 stars great math text 25 July 2006
By Chicago girl - Published on Amazon.com
Format: Paperback
I used this book at NYU in a graduate class on numerical linear algebra and it was great. The book is incredibly clear, starts from the basics and just goes from there. You won't be lost or feel like it has too little (and I usually have one of those two feelings about a math textbook).

The book is focused around matrix decompositions and does quite a bit of theoretical matrix algebra before it gets into accurate computation of decompositions, what this means and how various algorithms achieve it.

The theorems are clear and the proofs concise and easy to read.
7 of 7 people found the following review helpful
HASH(0x914a29b4) out of 5 stars A math textbook that's a joy to read 5 Jun. 2013
By K. Long - Published on Amazon.com
Format: Paperback Verified Purchase
Face it, most math textbooks are awful: boring to read, not much insight, little more than a compendium of definitions, theorems, proofs, and examples. Trefethen and Bau is an exception to that rule. Indeed, the field of numerical linear algebra is unusual in having available several top-notch textbooks: Golub and Van Loan, Stewart's two volumes, Saad's books on iterative methods, Demmel's introduction, Watkins' undergraduate level treatment, and T&B. All of these are excellent (and any student in numerical analysis should delve into all of them) but to my tastes T&B and Stewart are the standouts for insight and simply being fun to read.

If you're a student using T&B in a course, to use it effectively you need to understand that T&B is a book to be read carefully for understanding; it's not a typical textbook suited only for "mining" for examples and solutions to homework problems. My students have sometimes complained -- accurately -- that T&B is short on details and worked examples, and many of the proofs are just sketches. But that's a feature, not a bug: you can learn much by filling in the missing steps. This is book for reading, so take the time to read it, to think about what you've read, and to fill in the gaps; it's worth it. If you need some worked examples, Watkins has them in great detail and would be a good supplement to T&B (though see the caveat below).

The only minor gripe I have about T&B is that the order of topics (QR before LU before Cholesky) is unusual, which makes it a little awkward to coordinate with other books such as Watkins which do Cholesky before LU before QR.
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