Introduction to Scientific Computing (2nd Edition)

Author: (English) Heath
Publisher:
Publish Date: 2005-10-01
Features: This book comprehensively introduces numerical methods for solving various main problems in scientific computing, including linear and nonlinear equations, least squares methods, eigenvalues, optimization, interpolation, integration, ordinary differential equations, and partial differential equations, as well as fast Fourier transforms and random number generation. The book is designed for readers who use algorithms, focusing on teaching the underlying ideas and principles behind the algorithms rather than detailed analysis of the algorithms. It emphasizes concepts such as sensitivity and ill-conditioning, compares and evaluates different algorithms for the same problem, and enhances readers' appreciation of algorithms. For each type of problem, it provides specialized introductions and discussions on relevant mathematical software, including free software available on the Internet and commercial software platforms with copyright protection, for readers to choose from. The book is rich in examples and exercises, including over 160 illustrative examples, over 500 thought questions, over 240 practice problems, and over 200 numerical computation problems. This book can serve as a textbook or reference for graduate-level "Numerical Analysis" courses, and it holds high reference value for scientists and engineers who need to solve computational problems.