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Cambridge, England 1992 Hard cover 2nd Revised ed. Good. Sewn binding. Cloth over boards. 992 p. Contains: Illustrations.
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More About This Textbook
Overview
This is the greatly revised and greatly 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, this 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 textbook for scientists and engineers and an indispensable reference for anyone who works in scientific computing. The Second Edition is availabe in FORTRAN, the traditional language for numerical calculations and in the increasingly popular C language.
As with Numerical Recipes in C, the FORTRAN edition has been greatly revised to make this edition the most up to date handbook for those working with FORTRAN. Between both editions of Numerical Recipes, over 300,000 copies have been sold.
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Table of Contents
Legal matters; List of computer programs; 1. Preliminaries; 2. Solution of linear algebraic equations; 3. Interpolation and extrapolation; 4. Integration of functions; 5. Evaluation of functions; 6. Special functions; 7. Random numbers; 8. Sorting; 9. Root finding and nonlinear sets of equations; 10. Minimization or maximization of functions; 11. Eigensystems; 12. Fast Fourier transform; 13. Fourier and spectral applications; 14. Statistical description of data; 15. Modeling of data; 16. Integration of ordinary differential equations; 17. Two point boundary value problems; 18. Integral equations and inverse theory; 19. Partial differential equations; 20. Less-numerical algorithms; References; Index of programs and dependencies; General index.