Numerical Methods for Large Eigenvalue Problems

Yousef Saad

ISBN 10: 1611970725 / ISBN 13: 9781611970722

Published by Society for Industrial and Applied Mathematics,U.S., US, 2011

About this Item

This revised edition discusses numerical methods for computing the eigenvalues and eigenvectors of large sparse matrices. It provides an in-depth view of the numerical methods that are applicable for solving matrix eigenvalue problems that arise in various engineering and scientific applications. Each chapter was updated by shortening or deleting outdated topics, adding topics of more recent interest and adapting the Notes and References section. Significant changes have been made to Chapters 6 through 8, which describe algorithms and their implementations and now include topics such as the implicit restart techniques, the Jacobi-Davidson method and automatic multilevel substructuring.

Seller Inventory # LU-9781611970722

Bibliographic Details

• Title: Numerical Methods for Large Eigenvalue Problems
• Publisher: Society for Industrial and Applied Mathematics,U.S., US
• Publication Date: 2011
• Language: English
• ISBN 10: 1611970725
• ISBN 13: 9781611970722
• Binding: Paperback
• Condition: New
• Weight: 400 grams

About this title

Synopsis

This revised edition discusses numerical methods for computing the eigenvalues and eigenvectors of large sparse matrices. It provides an in-depth view of the numerical methods that are applicable for solving matrix eigenvalue problems that arise in various engineering and scientific applications. Each chapter was updated by shortening or deleting outdated topics, adding topics of more recent interest and adapting the Notes and References section. Significant changes have been made to Chapters 6 through 8, which describe algorithms and their implementations and now include topics such as the implicit restart techniques, the Jacobi–Davidson method and automatic multilevel substructuring.

About the Author

Yousef Saad is a College of Science and Engineering Distinguished Professor in the Department of Computer Science at the University of Minnesota. His current research interests include numerical linear algebra, sparse matrix computations, iterative methods, parallel computing, numerical methods for electronic structure and data analysis. He is a Fellow of SIAM and the AAAS.