The Matrix Eigenvalue Problem: GR and Krylov Subspace Methods

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After working on the reduction of IC interconnect networks for months, I am eager to find a book about matrix eigenvalue computations. Although there are several famous bibles in this field, like "The Algebraic Eigenvalue Problem" by James Wilkinson, they are not so up-to-date that some important topics like product eigenvalue problems are not covered. Also, matrices with special structures require dedicated algortihms to compute their eigenvalues efficiently. This book might be the best book which covers all the latest eigenvalue problems in a very traceable way. The other major advantage of this book is its well-designed exercises. Many theorems are proved in the exercises with step-by-step guidance. Actually, the exercises demonsrtate how the autohr proves/solves a theorem/problem. I indeed gain a lot of insight from the exercises! I recommend this book to anyone who wants to implement matrix eigenvalue computation algorithms by yourslef.

Author(s): David S. Watkins
Edition: 1
Publisher: Society for Industrial Mathematics
Year: 2007

Language: English
Pages: 451