Overview
- A monograph by a famous numerical analyst
- A classic in a revised and expanded edition
- Includes supplementary material: sn.pub/extras
Part of the book series: Springer Series in Computational Mathematics (SSCM, volume 27)
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Table of contents (9 chapters)
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Front Matter
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Back Matter
Keywords
About this book
This is the softcover reprint of a very popular hardcover edition, a revised version of the first edition, originally published by Prentice Hall in 1962 and regarded as a classic in its field. In some places, newer research results, e.g. results on weak regular splittings, have been incorporated in the revision, and in other places, new material has been added in the chapters, as well as at the end of chapters, in the form of additional up-to-date references and some recent theorems to give the reader some newer directions to pursue. The material in the new chapters is basically self-contained and more exercises have been provided for the readers. While the original version was more linear algebra oriented, the revision attempts to emphasize tools from other areas, such as approximation theory and conformal mapping theory, to access newer results of interest. The book should be of great interest to researchers and graduate students in the field of numerical analysis.
Authors and Affiliations
Bibliographic Information
Book Title: Matrix Iterative Analysis
Authors: Richard S. Varga
Series Title: Springer Series in Computational Mathematics
DOI: https://doi.org/10.1007/978-3-642-05156-2
Publisher: Springer Berlin, Heidelberg
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eBook Packages: Springer Book Archive
Copyright Information: Springer-Verlag Berlin Heidelberg 2000
Hardcover ISBN: 978-3-540-66321-8Published: 17 November 1999
Softcover ISBN: 978-3-642-05154-8Published: 21 December 2009
eBook ISBN: 978-3-642-05156-2Published: 05 December 2009
Series ISSN: 0179-3632
Series E-ISSN: 2198-3712
Edition Number: 2
Number of Pages: X, 358
Additional Information: Originally published by Prentice Hall, 1962
Topics: Algebra, Numerical Analysis, Linear and Multilinear Algebras, Matrix Theory