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《数值分析》(Numerical Recipes)3rd Edition含源代码
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软件简介:
- 上论坛找商业破解网站程序
- 源码使用如需帮助，请到论坛发帖！
非常推荐的一本好书！！
本书选材内容丰富，包括了当代科学计算过程中涉及的大量内容：求特殊函数值、随机数、排序、最优化、快速傅里叶变换、谱分析、小波变换、统计描述和数据建模、偏微分议程数值解、若乾编码算法和任意精度计算等。本书科学性和实用性统一，不仅对每种算法进行了数学分析和比较，而且根据作者经验对算法给出了评论和建议，并在此基础上提供了用C++语言编写的实用程序。
Co-authored by four leading scientists from academia and industry, Numerical Recipes, Third Edition starts with basic mathematics and computer science and proceeds to complete, working routines. Widely recognized as the most comprehensive, accessible and practical basis for scientific computing, this new edition incorporates more than 400 Numerical Recipes routines, many of them new or upgraded. The executable C++ code, now printed in color for easy reading, adopts an object-oriented style particularly suited to scientific applications. The whole book is presented in the informal, easy-to-read style that made earlier editions so popular.
New key features:
- 2 new chapters, 25 new sections, 25% longer than Second Edition
- Thorough upgrades throughout the text
- Over 100 completely new routines and upgrades of many more.
- New Classification and Inference chapter, including Gaussian mixture models, HMMs, hierarchical clustering, Support Vector Machines
- New Computational Geometry chapter covers KD trees, quad- and octrees, Delaunay triangulation, and algorithms for lines, polygons,triangles, and spheres
- New sections include interior point methods for linear programming,Monte Carlo Markov Chains, spectral and pseudospectral methods for PDEs,and many new statistical distributions
- An expanded treatment of ODEs with completely new routines Plus comprehensive coverage of
- linear algebra, interpolation, special functions, random numbers,nonlinear sets of equations, optimization, eigensystems, Fourier methods and wavelets, statistical tests, ODEs and PDEs, integral equations, and inverse theory And much, much more!
URL: http://www.amazon.com/exec/obidos/tg/detail/-/0521880688/
Contents
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 and selection;
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. Classification and inference;
17. Integration of ordinary differential equations;
18. Two point boundary value problems;
19. Integral equations and inverse theory;
20. Partial differential equations;
21. Computational geometry;
22. Less-numerical algorithms;
References.
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