| Details | | Publication Date: | 1993-01-01 | | Editor: | William H. Press | | Edition Description: | Illustrated |
| Size | | Length: | 994 pages | | Height: | 10.0 in | | Width: | 6.8 in | | Thickness: | 1.5 in | | Weight: | 52.8 oz |
Publisher's Note
The new and greatly expanded second edition of the highly popular Numerical Recipes in C features over 100 new routines and upgraded versions of the original routines. The book remains the most practical, comprehensive handbook of scientific computing available today.
This is the greatly revised and expanded Second Edition of the hugely popular Numerical Recipes: The Art of Scientific Computing. The product of a unique collaboration among four leading scientists in academic research and industry Numerical Recipes is a complete text and reference book on scientific computing. In a self-contained manner it proceeds from mathematical and theoretical considerations to actual practical computer routines. With over 100 new routines bringing the total to well over 300, plus upgraded versions of the original routines, the new edition remains the most practical, comprehensive handbook of scientific computing available today. Highlights of the new material include: A new chapter on integral equations and inverse methods Multigrid and other methods for solving partial differential equations Improved random number routines Wavelet transforms The statistical bootstrap method A new chapter on less-numerical algorithms including compression coding and arbitrary precision arithmetic. The book retains the informal easy-to-read style that made the first edition so popular, while introducing some more advanced topics. It is an ideal reference for scientists and engineers and indispensable to anyone who works in scientific computing. The Second Edition is available in the increasingly popular C language and in FORTRAN, the traditional language for numerical calculations. The C version takes advantage of many unique features of the C language including dynamic memory allocation, modularization, pointer reference to matrices, structured programming, and much more.
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