Numerical Methods for Large Eigenvalue Problems, Revised Edition
✍ Scribed by Yousef Saad
- Publisher
- SIAM
- Year
- 2011
- Tongue
- English
- Leaves
- 285
- Series
- Classics in Applied Mathematics
- Edition
- Revised edition
- Category
- Library
No coin nor oath required. For personal study only.
✦ Synopsis
This revised edition discusses numerical methods for computing 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 Each chapter was updated by shortening or deleting outdated topics, adding topics of more recent interest, and adapting the Notes and References section.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. Audience: This book is intended for researchers in applied mathematics and scientific computing as well as for practitioners interested in understanding the theory of numerical methods used for eigenvalue problems. It also can be used as a supplemental text for an advanced graduate-level course on these methods. Contents: Chapter One: Background in Matrix Theory and Linear Algebra; Chapter Two: Sparse Matrices; Chapter Three: Perturbation Theory and Error Analysis; Chapter Four: The Tools of Spectral Approximation; Chapter Five: Subspace Iteration; Chapter Six: Krylov Subspace Methods; Chapter Seven: Filtering and Restarting Techniques; Chapter Eight: Preconditioning Techniques; Chapter Nine: Non-Standard Eigenvalue Problems; Chapter Ten: Origins of Matrix Eigenvalue Problems
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This revised edition discusses numerical methods for computing 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 c
A detailed view of the numerical methods used to solve large matrix eigenvalue problems that arise in various engineering and scientific applications. The emphasis is on the more difficult nonsymmetric problems, but much of the important material for symmetric problems is also covered. The text cont
Второе издание полезной книги, выложенное автором на его сайте.<br/>http://www-users.cs.umn.edu/~saad/books.html.<br/>This is the second edition of a book published almost two decades ago by Manchester University Press (See below). The book is published by SIAM.<br/>SIAM, 2011 / xvi + 276 pages / So
This textbook presents a number of the most important numerical methods for finding eigenvalues and eigenvectors of matrices. The authors discuss the central ideas underlying the different algorithms and introduce the theoretical concepts required to analyze their behaviour. Several programming ex
<p>Eigenvalues and eigenvectors of matrices and linear operators play an important role when solving problems from structural mechanics and electrodynamics, e.g., by describing the resonance frequencies of systems, when investigating the long-term behavior of stochastic processes, e.g., by describin