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Numerical Recipes 3rd Edition: The Art of Scientific Computing 3rd Edition
- 2 new chapters, 25 new sections, 25% longer than Second Edition
- Thorough upgrades throughout the text
- Over 100 completely new routines and upgrades of many more.
- New Classification and Inference chapter, including Gaussian mixture models, HMMs, hierarchical clustering, Support Vector Machines
- New Computational Geometry chapter covers KD trees, quad- and octrees, Delaunay triangulation, and algorithms for lines, polygons, triangles, and spheres
- New sections include interior point methods for linear programming, Monte Carlo Markov Chains, spectral and pseudospectral methods for PDEs, and many new statistical distributions
- An expanded treatment of ODEs with completely new routines
- linear algebra, interpolation, special functions, random numbers, nonlinear sets of equations, optimization, eigensystems, Fourier methods and wavelets, statistical tests, ODEs and PDEs, integral equations, and inverse theory
- ISBN-100521880688
- ISBN-13978-0521880688
- Edition3rd
- PublisherCambridge University Press
- Publication dateSeptember 10, 2007
- LanguageEnglish
- Dimensions7.25 x 1.75 x 10 inches
- Print length1256 pages
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Editorial Reviews
Review
Computing Reviews
"… 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."
New Scientist
"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."
The Scientist
"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
Book Description
About the Author
Saul A. Teukolsky is H. A. Bethe Professor in Physics in the Radiophysics and Space Research Department of Cornell University.
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.
Brian P. Flannery is Science, Strategy and Programs Manager at Exxon Mobil Corporation.
Product details
- Publisher : Cambridge University Press; 3rd edition (September 10, 2007)
- Language : English
- Hardcover : 1256 pages
- ISBN-10 : 0521880688
- ISBN-13 : 978-0521880688
- Item Weight : 4.54 pounds
- Dimensions : 7.25 x 1.75 x 10 inches
- Best Sellers Rank: #122,941 in Books (See Top 100 in Books)
- #17 in Mathematical & Statistical Software
- #249 in Computer Science (Books)
- #927 in Mathematics (Books)
- Customer Reviews:
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The book is mainly useful for its discussion of the issues involved in numerical analysis, the presentation of algorithms, and -- to some extent -- the demonstration of the algorithms in code.
That said, the biggest weakness of this book is the code itself. The C++ programs appear to be direct translations of Fortran, bringing to mind the old joke that 'real programmers can write Fortran in any language'. The book would have been far more useful, and the implementations far easier to understand, if the algorithms had been simply written in pseudocode. The code is insufficiently commented, and the variable names are often hard to comprehend. In fact, the code in this book violates almost every precept laid down by Steve McConnell in his excellent -- and still relevant -- book Code Complete 2nd ed.
In that regard, the authors' concerns about potential copyright violations of their code are almost laughable; no sane programmer writing in C++ (or in Java or C#, or any other modern language, for that matter) would write his/her code the same way as presented in the book.
I give this a 4* rating because of how comprehensive this book is and the care the authors take to discuss implementation issues. But I almost knocked it down to 3* because of the horrible coding.
Aside from silly copyright restriction, it would not be even worth it - code is simply total garbage. Oftentimes, you are better off *not reading the code*, since it might confuse you. Bad naming conventions, sloppy practices abound.
Still, as far as actual content goes, this book is a gem. Down to point descriptions of rationale behind algorithms.
They are more than enough to get you going. Don't listen to detractors who denounce NR as "not professional enough" - meaning it does not contain the most esoteric implementations described in some journal by "experts".
It is easy to go beyond NR if you need to - but this book is a hundreds time better than academic numerical analysis textbooks who won't actually calculate anything in 600 pages.
On the negative side,
1) the physical book’s quality is not great, the binding easily breaks
2) the code, while efficient, is barely readable. It is old Fortran style with variables aaa, bbb etc. So you can copy the code, but will have hard time altering it for your needs.
3) on occasion the book does not contain the whole algorithm and prompts you to go online.
Well, I could go online without paying $100 for the book, and expected the book to be sufficient.
Having said this all, I’m still keeping it.
1) License: Forget about products. If you use this for a course, you can't reproduce any of the routines for your homework. If you did then the entire class should be booked for copy-right infringement.
2) Comments: Authors are extremely reluctant to comment their code. Out of blue variables pop-up. There is no pseudo-code for algorithms and routines are not commented.
3) Typos: There are lot of typos. More than you can imagine. Most of the routines miss ; { }.
4) Programming practice: If you have dealt with a good code base with just 1000 lines of code, you will get nausea and stomach cramps while analysis every single routine.
5) C++: This book is written in C and indexed as C++. There is no C/C++. There is C and there is C++. Authors don't give a cent about Containers, scoping, type safety, exceptions, etc.
6) Numerical Math: Common reason cite by scientific programmers is that this book cover math. The truth is it doesn't. This is more like "How to write brilliant algorithms in horrible c++ for Numerical Mathematicians." If you know the theory and find it difficult to express it in code, you will appreciate this one. However, if you don't learn good programming habits, you will be a jobless programmer.
Algorithms are brilliant and well structured topics. But neither can one key-in more than 10 programs nor can they publish better executions for this code base. Theren't books which are as broad as this one. It is the only reason every Computational Math student is forced to use it.



