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Numerical Recipes 3rd Edition: The Art of Scientific Computing 3rd Revised edition


Numerical Recipes 3rd Edition: The Art of Scientific Computing 3rd Revised edition

Hardback by Press, William H. (University of Texas, Austin); Teukolsky, Saul A. (Cornell University, New York); Vetterling, William T.; Flannery, Brian P.

Numerical Recipes 3rd Edition: The Art of Scientific Computing

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£84.99

ISBN:
9780521880688
Publication Date:
6 Sep 2007
Edition/language:
3rd Revised edition / English
Publisher:
Cambridge University Press
Pages:
1256 pages
Format:
Hardback
For delivery:
Estimated despatch 22 May 2024
Numerical Recipes 3rd Edition: The Art of Scientific Computing

Description

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.

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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