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Numerical Recipes 3rd Edition: The Art of Scientific Computing Hardcover – Sep 10 2007
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"This monumental and classic work is beautifully produced and of literary as well as mathematical quality. It is an essential component of any serious scientific or engineering library."
"... an instant 'classic,' a book that should be purchased and read by anyone who uses numerical methods ..."
American Journal of Physics
"... replete with the standard spectrum of mathematically pretreated and coded/numerical routines for linear equations, matrices and arrays, curves, splines, polynomials, functions, roots, series, integrals, eigenvectors, FFT and other transforms, distributions, statistics, and on to ODE's and PDE's ... delightful."
Physics in Canada
"... if you were to have only a single book on numerical methods, this is the one I would recommend."
EEE Computational Science & Engineering
"This encyclopedic book should be read (or at least owned) not only by those who must roll their own numerical methods, but by all who must use prepackaged programs."
"These books are a must for anyone doing scientific computing."
Journal of the American Chemical Society
"The authors are to be congratulated for providing the scientific community with a valuable resource."
"I think this is an incredibly valuable book for both learning and reference and I recommend it for any scientists or student in a numerate discipline who need to understand and/or program numerical algorithms."
International Association for Pattern Recognition
"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
The third edition of Numerical Recipes has wider coverage than ever before. New chapters cover classification and inference and computational geometry; new sections include MCMC, interior point methods, and an updated, expanded treatment of ODEs, all with completely new routines in C++. For more information, or to buy the book, visit www.cambridge.org/numericalrecipes. For support, or to subscribe to an online version, please visit www.nr.com.See all Product Description
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Top Customer Reviews
Later, I put together an application involving Delaunay Triangulation of many thousands of vertices, requiring a fast algorithm. For that, I turned to Knuth's Axioms and Hulls paper and subsequent book The Stanford Graphbase. I was very pleased to see that Chapter 21 on Computational Geometry includes a section on Delaunay Triangles and other useful routines.
I must admit that I was surprised to find that their code did not include data structures from the C++ Standard Template Library. Having made extensive use of STL methods in several projects of late, I was initially annoyed that a *certain* academic streak of stubbornness might have crept in. Afterall, why not take advantage of the fact that well-written and highly reuseable templates for commonly used data structures are available to all ANSI- and ISO-compliant C++ compiler users. Well, after reading the Preface and Chapter 1 it became clear that many of the numerical algorithms covered in the book do not require classes with the depth and complexity that are available in the STL. This was hard to swallow at first, but their use of smaller and more efficient structures with their own methods actually simplifies the code.
This is the essence of well crafted numerical techniques: keep things simple, keep things efficient, keep things flexible, and know the limits of each algorithm you implement. This is more than just an updated edition using the C++ language but also a very nice lesson in object-oriented techniques for serious number crunching programmers.
Most Helpful Customer Reviews on Amazon.com (beta)
I already owned a copy of "Numerical Recipes in C, 2nd Edition" (from 1992), so I was absolutely thrilled when I saw that the book had been updated in over 15 years. This is why I was so underwhelmed with the 3rd edition. As a previous reviewer noted, the vast majority of the book is largely unchanged.
As in previous editions, the authors do a great job of providing codes that cover the spectrum of topics encountered by researchers. As in previous editions, the authors still take the "give a man a fish" instead of the "teach a man to fish" method. This might seem like a negative but, in my opinion, this is why every scientist should own a copy of Numerical Recipes. Often, topics pop up that need immediate solving and one can often find a code for the topic in Numerical Recipes. As in previous editions, Numerical Recipes is really just an annotated code repository, with very stringent/restrictive licensing rules by the way!
However, as the authors note in the introduction, they made a conscious decision to fill pages with verbatim codes, not building insight into various topics. In my experience, the codes given in Numerical Recipes get the job done, but these tend to be simple and less efficient than other well-known algorithms.
As in previous editions, Numerical Recipes is a terrible pedagogical text. If you're interesting in understanding a particular topic, then get a special-purpose book.
If the authors went with some kind of traditional open-source license instead, that would be terrific. Right now, it looks like financial greed has gotten in the way of the dissemination of good ideas.
And don't give your code to a friend or coworker. You just violated the copyright.
Several coworkers have given me simulations with NR code buried in it. I can't use them. It is ILLEGAL!
Stop! Stop! Stop!
Use the GNU Scientific Library. It is free. And legal! And there is a free book on it. Use anything but NR.
Completely reorganized to reflect the book.
2.Solution of Linear Algebraic Equations
3. Interpolation and Extrapolation
3.7 Interpolation on a Scattered Data in Multidimensions
3.8 Laplace Interpolation
4. Integration of Functions
4.5 Quadrature by Variable Transformation
4.8 Adaptive Quadrature
5. Evaluation of Functions
6. Special Functions
6.10 Generalized Fermi-Dirac Integrals
6.11 Inverse of the Function xlog(x)
6.14 Statistical Functions
7. Random Numbers
7.2 Completely Hashing a Large Array
7.3 Deviates from Other Distributions
7.4 Multivariate Normal Deviates
7.5 Linear Feedback Shift Registers
7.6 Hash Tables and Hash Memories
9. Root Finding and Nonlinear Sets of Equations
10. Minimization or Maximization of Functions
10.1 Initially Bracketing a Minimum
10.6 Line Methods in Multidimensions
10.11 Linear Programming: Interior-Point Methods
10.13 Dynamic Programming
11.2 Real Symmetric Matrices
11.6 Real Nonsymmetric Matrices
12. Fast Fourier Transform
13. Fourier and Spectral Applications
14. Statistical Description of Data
14.7 Information-Theoretic Properties of Distributions
15. Modeling of Data
15.8 Markov Chain Monte Carlo
15.9 Gaussian Process Regression
16. Classification and Inference (NEW CHAPTER)
17. Integration of Ordinary Differential Equations
17.7 Stochastic Simulation of Chemical Reaction Networks
18. Two-Point Boundary Value Problems
19. Integral Equations and Inverse Theory
20. Partial Differential Equations
20.7 Spectral Methods
21. Computational Geometry (NEW CHAPTER)
22. Less-Numerical Algorithms
22.1 Plotting Simple Graphs
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