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Matrix Computations (Johns Hopkins Series in the Mathematical Sciences)

Matrix Computations (Johns Hopkins Series in the Mathematical Sciences)
By Gene H. Golub, Charles F. Van Loan

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Product 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.


Product Details

  • Amazon Sales Rank: #193890 in Books
  • Published on: 1996-10-15
  • Original language: English
  • Number of items: 1
  • Binding: Paperback
  • 728 pages

Editorial Reviews

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'

Review

"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, reviewing a previous edition or volume



"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, reviewing a previous edition or volume



"The authors have rewritten and clarified many of the proofs and derivations from the first edition. They have also added new topics such as Arnoldi iteration, domain decomposition methods, and hyperbolic downdating. Clearly the second edition is an invaluable reference book that should be in every university library. With the new proofs and derivations, it should remain the text of choice for graduate courses in matrix computations" -- Image: Bulletin of the International Linear Algebra Society, reviewing a previous edition or volume

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.


Customer Reviews

Best Matrix Book Ever!!!5
This book has just about everything:

High quality theoretical foundations, good solid code for Matlab and some fortran routines, I like the fact the authors think about loops and iterators the way I do, as a programmer, but also have the time to write out the material as a mathematician, often these two things are totally seperate in pure math and programming books.

Simply a must for anyone doing any matrix programming, as the ideas and implementations are easily portable to other matrix/array based langauges such as Gauss and R.

A great reference book for doing numerical analysis.5
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 ill-conditioned matrices is great.

THE CLASSIC reference for matrix computations!5
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.