Inverse Eigenvalue Problems: Theory, Algorithms, and Applications

Hardcover | July 16, 2005

byMoody Chu, Gene Golub

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Inverse eigenvalue problems arise in a remarkable variety of applications and associated with any inverse eigenvalue problem are two fundamental questions--the theoretical issue of solvability and the practical issue of computability. Both questions are difficult and challenging. In this text,the authors discuss the fundamental questions, some known results, many applications, mathematical properties, a variety of numerical techniques, as well as several open problems.This is the first book in the authoritative bNumerical Mathematics and Scientific Computation/b series to cover numerical linear algebra, a broad area of numerical analysis. Authored by two world-renowned researchers, the book is aimed at graduates and researchers in applied mathematics, engineeringand computer science and makes an ideal graduate text.

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Inverse eigenvalue problems arise in a remarkable variety of applications and associated with any inverse eigenvalue problem are two fundamental questions--the theoretical issue of solvability and the practical issue of computability. Both questions are difficult and challenging. In this text,the authors discuss the fundamental questio...

Moody Chu is currently an editor of the SIAM Journal on Matrix Analysis and Applications. He is a dedicated educator and has won outstanding teaching awards. Gene Golub has been and continues to be the editor of several important journals (Numerische Mathematik, Linear Algebra and Its Applications, Acta Numerica, etc.) in the field. H...

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Format:HardcoverDimensions:406 pages, 9.21 × 6.14 × 1.04 inPublished:July 16, 2005Publisher:Oxford University PressLanguage:English

The following ISBNs are associated with this title:

ISBN - 10:0198566646

ISBN - 13:9780198566649

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Table of Contents

Preface1. Introduction2. Applications3. Parameterized Inverse Eigenvalue Problems4. Structured Inverse Eigenvalue Problems5. Partially Described Inverse Eigenvalue Problems6. Least Squares Inverse Eigenvalue Problems7. Spectrally Constrained Approximation8. Structured Low Rank Approximation9. Group Orbitally Constrained ApproximationIndex