9780198506720-0198506724-Orthogonal Polynomials: Computation and Approximation (Numerical Mathematics and Scientific Computation)

Orthogonal Polynomials: Computation and Approximation (Numerical Mathematics and Scientific Computation)

ISBN-13: 9780198506720
ISBN-10: 0198506724
Author: Walter Gautschi
Publication date: 2004
Publisher: Oxford University Press
Format: Hardcover 312 pages
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Book details

ISBN-13: 9780198506720
ISBN-10: 0198506724
Author: Walter Gautschi
Publication date: 2004
Publisher: Oxford University Press
Format: Hardcover 312 pages

Summary

Orthogonal Polynomials: Computation and Approximation (Numerical Mathematics and Scientific Computation) (ISBN-13: 9780198506720 and ISBN-10: 0198506724), written by authors Walter Gautschi, was published by Oxford University Press in 2004. With an overall rating of 4.5 stars, it's a notable title among other AI & Machine Learning (Computer Science) books. You can easily purchase or rent Orthogonal Polynomials: Computation and Approximation (Numerical Mathematics and Scientific Computation) (Hardcover) from BooksRun, along with many other new and used AI & Machine Learning books and textbooks. And, if you're looking to sell your copy, our current buyback offer is $0.3.

Description

This is the first book on constructive methods for, and applications of orthogonal polynomials, and the first available collection of relevant Matlab codes. The book begins with a concise introduction to the theory of polynomials orthogonal on the real line (or a portion thereof), relative to a positive measure of integration. Topics which are particularly relevant to computation are emphasized. The second chapter develops computational methods for generating the coefficients in the basic three-term recurrence relation. The methods are of two kinds: moment-based methods and discretization methods. The former are provided with a detailed sensitivity analysis. Other topics addressed concern Cauchy integrals of orthogonal polynomials and their computation, a new discussion of modification algorithms, and the generation of Sobolev orthogonal polynomials. The final chapter deals with selected applications: the numerical evaluation of integrals, especially by Gauss-type quadrature methods, polynomial least squares approximation, moment-preserving spline approximation, and the summation of slowly convergent series. Detailed historic and bibliographic notes are appended to each chapter. The book will be of interest not only to mathematicians and numerical analysts, but also to a wide clientele of scientists and engineers who perceive a need for applying orthogonal polynomials.

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