Computational Science and Engineering

by Gilbert Strang

Encompasses the full range of computational science and engineering from modelling to solution, both analytical and numerical. It develops a framework for the equations and numerical methods of applied mathematics. Gilbert Strang has taught this material to thousands of engineers and scientists (and many more on MIT's OpenCourseWare 18.085-6). His experience is seen in his clear explanations, wide range of examples, and teaching method. The book is solution-based and not formula-based: it integrates analysis and algorithms and MATLAB codes to explain each topic as effectively as possible. The topics include applied linear algebra and fast solvers, differential equations with finite differences and finite elements, Fourier analysis and optimization. This book also serves as a reference for the whole community of computational scientists and engineers. Supporting resources, including MATLAB codes, problem solutions and video lectures from Gilbert Strang's 18.085 courses at MIT, are provided at math.mit.edu/cse.

Genres: Mathematics, Science, Textbooks, Programming, Computer Science, Engineering

750 pages, Hardcover

First published November 1, 2007

About the author

William Gilbert Strang (born November 27, 1934), usually known as simply Gilbert Strang or Gil Strang, is an American mathematician, with contributions to finite element theory, the calculus of variations, wavelet analysis and linear algebra. He has made many contributions to mathematics education, including publishing seven mathematics textbooks and one monograph. Strang is the MathWorks Professor of Mathematics at the Massachusetts Institute of Technology. He teaches Introduction to Linear Algebra and Computational Science and Engineering and his lectures are freely available through MIT OpenCourseWare.

Reviews

[Peter Braden · Rating 1 out of 5]

Strang starts his introduction by claiming that to teach applied mathematics you need to find a pattern or a structure.

Sadly he doesn’t take his own advice and this meandering sprawl of a textbook, with its anecdotes about mathematical beauty, is a maze. He doesn’t provide any practicable context for the techniques until far too late.

Perhaps it works in conjunction with a course, but as a standalone textbook it’s impenetrable.

[Gavin Ridley · Rating 5 out of 5]

I wish this was the textbook for my numerical analysis class in engineering! The book is not formulaic in any way, and gives derivations which aid in understanding the materials. It leaves out Monte Carlo though, an arguably important topic in numerical analysis.