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Numerical Recipes 3rd Edition

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William H. Press 作者
Cambridge University Press
译者
2007-9-6 出版日期
1256 页数
GBP 64.99 价格
Hardcover
丛书系列
9780521880688 图书编码

Numerical Recipes 3rd Edition 在线电子书 图书标签: 数学  数值计算  算法  计算机  数值计算方法  numerical  计算机科学  Computation   


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发表于2024-11-05


Numerical Recipes 3rd Edition 在线电子书 epub 下载 mobi 下载 pdf 下载 txt 下载 2024

Numerical Recipes 3rd Edition 在线电子书 epub 下载 mobi 下载 pdf 下载 txt 下载 2024

Numerical Recipes 3rd Edition 在线电子书 pdf 下载 txt下载 epub 下载 mobi 下载 2024



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Numerical Recipes 3rd Edition 在线电子书 图书描述

Do you want easy access to the latest methods in scientific computing? This greatly expanded third edition of Numerical Recipes has it, with wider coverage than ever before, many new, expanded and updated sections, and two completely new chapters. The executable C++ code, now printed in colour for easy reading, adopts an object-oriented style particularly suited to scientific applications. 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 whole book is presented in the informal, easy-to-read style that made earlier editions so popular. 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 to subscribe to an online version, please visit www.nr.com.

• Most comprehensive book available on scientific computing, now updated • New routines for classification and inference HMMs and SVMs, computational geometry, ODEs, interior point methods for linear programming, and MCMC • Over 600,000 Numerical Recipes products in print

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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