Selected Product:
| Numerical Recipes 3rd Edition: The Art of Scientific Computing
Hardcover
Edition: 3
Author: William H. Press, Saul A. Teukolsky, William T.
Publisher: Cambridge University Press
Release Date: 2007-09-10
ISBN-10: 0521880688
ISBN-13: 9780521880688
List Price: $80.00
Average Customer Rating:
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Summaries and Customer Reviews are supplied by Amazon.com
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 color 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.
Continues to improve
| Customer Rating: | | I have owned copies of the first two editions of this book and I was impressed with the updates to this third edition. There are several new topics and the existing areas have been updated. I was able to use some of the statistical code in a production piece of software two days after receiving this new version. The website associated with the book also has a nice feature that figures out the header dependencies for you. |
Valuable book, but not worth an upgrade
| Customer Rating:  | Bottom line up front: Every computational scientist should own a copy of Numerical Recipes but, if you already own a previous version, then don't bother upgrading.
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.
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Quickly switching your matlab routines to cpp
| Customer Rating: | I'm an engineer and I like to create my own solutions in Matlab, since it's easy to program. The problem arises when you want to deliver a nice and fast cpp executable.
This is where this books enters, with fast, easy to understand, operational code.
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The perfect book
| Customer Rating: | | The perfect book for me, because I am interested in mathematics and also in computer programing. |
Essential book on scientific computing
| Customer Rating: | Fifteen years after its previous edition, this peerless book on scientific computing has been upgraded with some very welcome changes. Not only have some advances in scientific computing been incorporated, the explanations are even clearer and more detailed than before. More importantly, the code has been reworked so that it is better than it was in the previous edition. I don't agree with the other reviewer that "it is getting worse". However, it still does seem like C++ code that was written by a Fortran programmer who just doesn't want to let go of the past, although I'd have to say that the code has broken away from the Fortran-like structure of previous editions to some degree. If you do scientific computing at all, this new edition is a must have. Below I detail what is different in this new third edition versus the previous 1992 edition. There are a very few sections that were deleted. I don't mention them. Instead I list any sections or chapters that have been added.
1. Preliminaries
Completely reorganized to reflect the book.
2.Solution of Linear Algebraic Equations
THE SAME
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
THE SAME
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
8. Sorting
THE SAME
9. Root Finding and Nonlinear Sets of Equations
THE SAME
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. Eigensystems
11.2 Real Symmetric Matrices
11.6 Real Nonsymmetric Matrices
12. Fast Fourier Transform
THE SAME
13. Fourier and Spectral Applications
THE SAME
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
THE SAME
19. Integral Equations and Inverse Theory
THE SAME
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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