Matrix Computations

by Gene H Golub, Van Loan, Charles F

The fourth edition of Gene H. Golub and Charles F. Van Loan's classic is an essential reference for computational scientists and engineers in addition to researchers in the numerical linear algebra community. Anyone whose work requires the solution to a matrix problem and an appreciation of its mathematical properties will find this text useful and engaging. This revision is a cover-to-cover expansion and renovation of the third edition. It now includes an introduction to tensor computations and brand new sections on • fast transforms• parallel LU• discrete Poisson solvers• pseudospectra• structured linear equation problems• structured eigenvalue problems• large-scale SVD methods• polynomial eigenvalue problems Matrix Computations is packed with challenging problems, insightful derivations, and pointers to the literature—everything needed to become a matrix-savvy developer of numerical methods and software.

Genres: Mathematics, Reference

781 pages, Kindle Edition

First published December 27, 2012

Reviews

[Tinwerume · Rating 3 out of 5]

It's a poorly written brick but it does actually have the relevant algorithms.

To expand: a lot of the most important linear algebra algorithms basically don't _have_ a writeup besides in this book. You could read the BLAS or LAPACK source code, you can find random blog posts and presentations here and there, but this is pretty much the only complete reference for how to do linear algebra in a computationally efficient way. It is bad at doing that relative to how good descriptions of algorithms _can_ be, but afaik it's pretty much the only game in town.