数値計算のレシピソースコード（第３版）<br>Numerical Recipes with Source Code CD-ROM 3rd Edition : The Art of Scientific Computing （3RD）

数値計算のレシピソースコード（第３版）
Numerical Recipes with Source Code CD-ROM 3rd Edition : The Art of Scientific Computing （3RD）

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  • ページ数 1256 p.
  • 言語 ENG
  • 商品コード 9780521884075
  • DDC分類 518.0285

基本説明

ベストセラーテキスト５年振りの改訂版。
The power of Numerical Recipes is now available to C++ users. Completely self-contained and fully compliant with the new ANSI/ISO C++ standard, the book features more than 300 supreme routines that provide a rock-solid basis for Scientific Computing of every kind.

Full Description

This book/CD bundle of the greatly expanded third edition of Numerical Recipes now has wider coverage than ever before, many new, expanded and updated sections, and two completely new chapters. Co-authored by four leading scientists from academia and industry, Numerical Recipes starts with basic mathematics and computer science and proceeds to complete, working routines. The informal, easy-to-read style that made earlier editions so popular is kept throughout. Highlights of the new material include: a new chapter on classification and inference, Gaussian mixture models, HMMs, hierarchical clustering, and SVMs; a new chapter on computational geometry, covering KD trees, quad- and octrees, Delaunay triangulation, and algorithms for lines, polygons, triangles, and spheres; interior point methods for linear programming; MCMC; an expanded treatment of ODEs with completely new routines; and many new statistical distributions. For support or further licence information please visit www.nr.com.

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.