Numerical Linear Algebra: An Introduction

Numerical Linear Algebra: An Introduction

by Holger Wendland
ISBN-10:
131660117X
ISBN-13:
9781316601174
Pub. Date:
11/16/2017
Publisher:
Cambridge University Press
ISBN-10:
131660117X
ISBN-13:
9781316601174
Pub. Date:
11/16/2017
Publisher:
Cambridge University Press
Numerical Linear Algebra: An Introduction

Numerical Linear Algebra: An Introduction

by Holger Wendland
$49.99
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Overview

This self-contained introduction to numerical linear algebra provides a comprehensive, yet concise, overview of the subject. It includes standard material such as direct methods for solving linear systems and least-squares problems, error, stability and conditioning, basic iterative methods and the calculation of eigenvalues. Later chapters cover more advanced material, such as Krylov subspace methods, multigrid methods, domain decomposition methods, multipole expansions, hierarchical matrices and compressed sensing. The book provides rigorous mathematical proofs throughout, and gives algorithms in general-purpose language-independent form. Requiring only a solid knowledge in linear algebra and basic analysis, this book will be useful for applied mathematicians, engineers, computer scientists, and all those interested in efficiently solving linear problems.

Product Details

ISBN-13: 9781316601174
Publisher: Cambridge University Press
Publication date: 11/16/2017
Series: Cambridge Texts in Applied Mathematics , #56
Pages: 418
Product dimensions: 5.98(w) x 8.94(h) x 0.98(d)

About the Author

Holger Wendland holds the Chair of Applied and Numerical Analysis at the Universität Bayreuth, Germany. He works in the area of Numerical Analysis and is the author of two books, Scattered Data Approximation (Cambridge, 2005) and Numerische Mathematik (2004, with Robert Schaback).

Table of Contents

Part I. Preliminaries: 1. Introduction; 2. Error, stability and conditioning; Part II. Basic Methods: 3. Direct methods for solving linear systems; 4. Iterative methods for solving linear systems; 5. Calculation of eigenvalues; Part III. Advanced Methods: 6. Methods for large sparse systems; 7. Methods for large dense systems; 8. Preconditioning; 9. Compressed sensing; References; Index.
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