A First Course in Numerical Analysis: Second Edition

By Philip Rabinowitz and Anthony Ralston

Book Overview

This outstanding text by two well-known authors treats numerical analysis with mathematical rigor, but presents relatively few theorems and proofs. Oriented toward computer solutions of problems, it stresses errors in methods and computational efficiency, and it compares different solutions to the same problem. Following an introductory chapter on sources of error and computer arithmetic, the text covers such topics as approximation and algorithms, interpolation, numerical differentiation and numerical quadrature, the numerical solution of ordinary differential equations, functional approximation by least squares and by minimum-maximum error techniques, the solution of nonlinear equations and of simultaneous linear equations, and the calculation of eigenvalues and eigenvectors of matrices. This second edition also includes discussions of spline interpolation, adaptive integration, the fast Fourier transform, the simplex method of linear programming, and simple and double QR algorithms. Problems -- some strictly mathematical, others requiring a computer -- appear at the end of each chapter.

• Format: Paperback
• Language: English
• ISBN: 048641454X
• ISBN13: 9780486414546
• Release Date: February 2001
• Publisher: Dover Publications
• Length: 640 Pages
• Weight: 1.48 lbs.
• Dimensions: 1.2" x 5.4" x 8.4"

Customer Reviews

5 Stars for undergrads

If you are looking in to 3d Nurbs buy this book. If you are looking to build a robot from scratch buy this book. It may mean taking calculus and linear algebra but the algorithms are very advanced and quick. This is the math that every corporation would like you to have if you are an engineer. Plus it helps you understand many of the mathematicians. After reading this book you have excellent under pinning for your name. P.S. This may be good for white hatter as well but I don't know since I am not into cryptography. P.P.S. Did you always think that Sin() was a magical function? Well you will learn more than you every thought possible with this book. The optimization on you code can go through the roof. Plus this seems to be (but I still have not confirmed) a good way of understanding O notation and not to mention NP complete algorithms (Such what classifies a NP Complete problem).

A classic and a bargain at that

I lost my original copy during my last move. Therefore, I was overjoyed that an inexpensive paperback version had been printed. A must for the numerical analyst's library.

good intermediate text on numerical analysis

This is a good intermediate text on numerical analysis. The development of the underlying real variable theory is much more rigorous than the closely related and more recent text "Numerical Recipes in C". Also, there is more attention paid to function theoretic considerations such as notions of continuity and compactness. This is basically an introductory numerical functional analysis textbook. There are numerous good examples sprinkled throughout the text. To get the most out of this book, you need a working knowledge of advanced calculus, real analysis and linear algebra.

Simply the best you can get (at this price)

This is the republication of the 2nd edition published by McGraw-Hill, 1978, with minor corrections. This Dover edition also includes 50 pages of Hints and Answers to Problems, which is very helpful. It is one of the 14 reference books listed in the Numerical Recipe in C: The Art of Scientific Computing, and the authors of the Recipe book says, of the 14 books, "These are the books that we like to have within easy reach." A. Ralston, of SUNY Buffalo, also co-wrote a book, Discrete Algorithmic Mathematics(DAM), which is easy and fun to read. But I am puzzled by the words - "Well-known and highly regarded even by those who have never used it." - on the back cover of the A K Peters edition of DAM. What do they mean?