SIAM, 2012. — 429 p. — ISBN: 9781611972450This revised edition of a classic textbook provides a complete guide to the calculation of eigenvalues of matrices. Written at an accessible level, this modern exposition of the subject presents fundamental aspects of the spectral theory of linear operators in finite dimension. Unique features of this book include a treatment of the convergence of eigensolvers based on the notion of the gap between invariant subspaces, and coverage of the impact of the high nonnormality of a matrix on its eigenvalues. Also included is a new chapter uncovering reasons why matrices are fundamental tools for the information processing that takes place in the dynamical evolution of systems. Some of these ideas appear in print for the first time. The book's primary use is as a course text for undergraduate students in mathematics, applied mathematics, physics, and engineering. It is also a useful reference for researchers and engineers in industry.Contents Preface to the classics edition Preface Preface to the English edition Notation List of errata Supplements from linear algebra Elements of spectral theory Why compute eigenvalues? Error analysis Foundations of methods for computing eigenvalues Numerical methods for large matrices Chebyshev's iterative methods Polymorphic information processing with matrices Appendix. Solution to exercises Appendix. References for exercises References Index.
Чтобы скачать этот файл зарегистрируйтесь и/или войдите на сайт используя форму сверху.