Numerical Recipes 3rd Edition
The Art of Scientific Computing

The essential text and reference for modern scientific computing now also covers computational geometry, classification and inference, and much more.

William H. Press (Author), Saul A. Teukolsky (Author), William T. Vetterling (Author), Brian P. Flannery (Author)

9780521880688, Cambridge University Press

Hardback, published 6 September 2007

1256 pages, 37 tables
26.2 x 19 x 4.5 cm, 2.06 kg

'The attractive style of the text and the availability of the codes ensured the popularity of the previous editions and also recommended this recent volume to different categories of readers, more or less experienced in numerical computation.' Octavian Pastravanu, Zentralblatt MATH

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.

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.

Subject Areas: Maths for engineers [TBJ], Maths for scientists [PDE], Applied mathematics [PBW], Numerical analysis [PBKS]