Scientific Computing: An Introductory Survey

by Michael T. Heath

Presents an overview of numerical methods for solving the major problems in scientific computing, including linear and nonlinear equations, least squares, eigenvalues, optimization, interpolation, integration, ordinary and partial differential equations, fast Fourier transforms, and random number generators.

Genres: Science, Computer Science, Mathematics, Engineering, Textbooks, Reference, Physics

563 pages, Hardcover

First published December 1, 1996

Reviews

[Dr M · Rating 3 out of 5]

The subtitle to Heath's book on numerical methods for scientific computing is "an Introductory Survey". This is almost an auto-review. Brevity is simultaneously the book's strength and its weakness. Scientific Computing is not so much a comprehensive textbook as a collection of introductions to the central ideas of the most important, elementary numerical methods for linear algebra, calculus, differential equations and non-linear equations. As such it is a splendid work to turn to when you need to get a rough idea of available methods for any given type of problem, or when you need a quick overview of the basics of some method. However, the descriptions Heath gives us are so brief and lacking in details, examples and explanations that any in-depth learning, let alone understanding becomes well nigh impossible. Also, this book gives very few hints on how to implement the methods in practice.

While Scientific Computing quickly becomes insufficient as a stand-alone resource for numerical methods, this should not be taken to mean that the book is bad. It certainly is not; it is very useful for quickly reading up on a (set of) method(s). Often, this is all one needs, while on other occasions, it serves as a useful guide to what to read in-depth about in more detailed texts.

Scientific Computin deserves its place on the shelf beside my computer at work and is often the first book I turn to. There are probably several other, and possibly newer, books on numerical analysis that can serve the same purpose, but I like Scientific Computin because Heath avoids the mistake of trying to do everything. The book calls itself an introductory survey, and that is exactly what you get, nothing more (though sometimes a little less, but I can live with that if I also have access to other texts).

[Antonietta · Rating 5 out of 5]

Great book about numerical analysis. Favorite quote: "We cannot live without approximations"! :)

[Gregory · Rating 4 out of 5]

This is not a bad text book. It covers a lot of material and is pretty general. However there are also a lot of examples to help make things concrete. My only compliant was there are a good number of typos. Since this is the sort of thing I don't normally notice I figure there must be a lot more than I saw.