Overview
- New edition provides emphasis on the algebraic structure of linear iteration, not usually included in most literature
- Completely renewed references
- Content grew out of a series of lectures given by author
- Extensive and useful appendices included
- Includes supplementary material: sn.pub/extras
Part of the book series: Applied Mathematical Sciences (AMS, volume 95)
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About this book
The necessary amount of work increases dramatically with the size of systems, so one has to search for algorithms that most efficiently and accurately solve systems of, e.g., several million equations. The choice of algorithms depends on the special properties the matrices in practice have. An important class of large systems arises from the discretization of partial differential equations. In this case, the matrices are sparse (i.e., they contain mostly zeroes) and well-suited to iterative algorithms.
The first edition of this book grew out of a series of lectures given by the author at the Christian-Albrecht University of Kiel to students of mathematics. The second edition includes quite novel approaches.
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Keywords
Table of contents (14 chapters)
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Linear Iterations
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Semi-Iterations and Krylov Methods
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Special Iterations
Authors and Affiliations
About the author
Bibliographic Information
Book Title: Iterative Solution of Large Sparse Systems of Equations
Authors: Wolfgang Hackbusch
Series Title: Applied Mathematical Sciences
DOI: https://doi.org/10.1007/978-3-319-28483-5
Publisher: Springer Cham
eBook Packages: Mathematics and Statistics, Mathematics and Statistics (R0)
Copyright Information: Springer International Publishing Switzerland 2016
Hardcover ISBN: 978-3-319-28481-1Published: 01 July 2016
Softcover ISBN: 978-3-319-80360-9Published: 31 May 2018
eBook ISBN: 978-3-319-28483-5Published: 21 June 2016
Series ISSN: 0066-5452
Series E-ISSN: 2196-968X
Edition Number: 2
Number of Pages: XXIII, 509
Number of Illustrations: 15 b/w illustrations, 11 illustrations in colour
Topics: Numerical Analysis, Linear and Multilinear Algebras, Matrix Theory, Partial Differential Equations