Numerical Recipes

Press, William H.William H. Press holds the Raymer Chair in Computer Sciences and Integrative Biology at the University of Texas at Austin.Teukolsky, Saul A.Saul A. Teukolsky is H. A. Bethe Professor in Physics in the Radiophysics and Space Research Department of Cornell University.Vetterling, William T.William Vetterling is a Research Fellow and Director of the Image Science Laboratory at ZINK Imaging, LLC in Waltham, MA. His career includes eight years on the physics faculty at Harvard and 20 years of numerical modeling and laboratory research on digital imaging at Polaroid Corporation.Flannery, Brian P.Brian P. Flannery is Science, Strategy and Programs Manager at Exxon Mobil Corporation.

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 nr.com.

The third edition of Numerical Recipes has wider coverage than ever before, with two new chapters, and many other expanded and updated sections. The executable object-oriented C++ code for all the routines is now printed in colour for easy reading.
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
- Many new statistical distributions

The third edition of Numerical Recipes has wider coverage than ever before, with two new chapters, and many other expanded and updated sections. The executable object-oriented C++ code for all the routines is now printed in colour for easy reading. 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 • Many new statistical distributions For more information, or to buy the book, visit cambridge.org/numericalrecipes. For support, or to subscribe to an online version, please visit nr.com.

From the 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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