Overview
- Contains an overview of state-of-the-art Krylov subspace methods including new theoretical convergence results
- Emphasis is placed on the construction of examples with prescribed convergence histories for many of the described methods
- Matlab codes included for most of the described methods and techniques
- New results are presented in the context of a unifying framework that are valid for classes of methods (so-called quasi-minimum residual and quasi-orthogonal residual methods)
- Contains descriptions of important methods not treated in previous books
Part of the book series: Springer Series in Computational Mathematics (SSCM, volume 57)
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About this book
This book can be useful for both practitioners and for readers who are more interested in theory. Together with a review of the state-of-the-art, it presents a number of recent theoretical results of the authors, some of them unpublished, as well as a few original algorithms. Some of the derived formulas might be useful for the design of possible new methods or for future analysis. For the more applied user, the book gives an up-to-date overview of the majority of the available Krylov methods for nonsymmetric linear systems, including well-known convergence properties and, as we said above, template codes that can serve as the base for more individualized and elaborate implementations.
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Keywords
Table of contents (13 chapters)
Authors and Affiliations
Bibliographic Information
Book Title: Krylov Methods for Nonsymmetric Linear Systems
Book Subtitle: From Theory to Computations
Authors: Gérard Meurant, Jurjen Duintjer Tebbens
Series Title: Springer Series in Computational Mathematics
DOI: https://doi.org/10.1007/978-3-030-55251-0
Publisher: Springer Cham
eBook Packages: Mathematics and Statistics, Mathematics and Statistics (R0)
Copyright Information: Springer Nature Switzerland AG 2020
Hardcover ISBN: 978-3-030-55250-3Published: 02 October 2020
Softcover ISBN: 978-3-030-55253-4Published: 03 October 2021
eBook ISBN: 978-3-030-55251-0Published: 02 October 2020
Series ISSN: 0179-3632
Series E-ISSN: 2198-3712
Edition Number: 1
Number of Pages: XIV, 686
Number of Illustrations: 184 b/w illustrations
Topics: Numerical Analysis