Inverse Eigenvalue Problems

Theory, Algorithms, and Applications

AvMoody Chu,Gene Golub

Inbunden, Engelska, 2005

Del i serien Numerical Mathematics and Scientific Computation

1 767 kr

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Beskrivning

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 Numerical Mathematics and Scientific Computation 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, engineering and computer science and makes an ideal graduate text.

Produktinformation

Utgivningsdatum:2005-06-16
Mått:163 x 242 x 26 mm
Vikt:750 g
Format:Inbunden
Språk:Engelska
Serie:Numerical Mathematics and Scientific Computation
Antal sidor:406
Förlag:OUP OXFORD
ISBN:9780198566649

Utforska kategorier

Mer om författaren

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. He is a member of the National Academy of Engineering (1990) and of the National Academy of Sciences. He holds more than a dozen of Honorary Degrees or Honorary Fellows from around the world. He is a dedicated educators and has won outstanding teaching awards.

Recensioner i media

A valuable tool for postgraduates, engineers and mathematicians in the area.

Innehållsförteckning

Preface ; 1. Introduction ; 2. Applications ; 3. Parameterized Inverse Eigenvalue Problems ; 4. Structured Inverse Eigenvalue Problems ; 5. Partially Described Inverse Eigenvalue Problems ; 6. Least Squares Inverse Eigenvalue Problems ; 7. Spectrally Constrained Approximation ; 8. Structured Low Rank Approximation ; 9. Group Orbitally Constrained Approximation ; Index