Largescale problems of engineering and scientific computing often require
solutions of eigenvalue and related problems. This book gives a unified
overview of theory, algorithms, and practical software for eigenvalue problems.
The material is accessible for the first
time to experts as well as many nonexpert users who need to choose the best
stateoftheart algorithms and software for their problems. Using an informal
decision tree, just enough theory is introduced to identify the relevant
mathematical structure that determines the best algorithm for each problem.
The algorithm "leaves" of the decision tree range
from the classical QR algorithm, which is most suitable for small dense
matrices, to iterative algorithms for very large generalized eigenvalue
problems. Algorithms are presented in a unified style as templates, with
different levels of detail suitable for readers ranging from beginning
students to experts.
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Acknowledgments



Royalties from the sale of this book are contributed to the SIAM
Student Travel Fund.

