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Inverse Eigenvalue ProblemsTheory, Algorithms, and Applications$
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Moody Chu and Gene Golub

Print publication date: 2005

Print ISBN-13: 9780198566649

Published to Oxford Scholarship Online: September 2007

DOI: 10.1093/acprof:oso/9780198566649.001.0001

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LEAST SQUARES INVERSE EIGENVALUE PROBLEMS

LEAST SQUARES INVERSE EIGENVALUE PROBLEMS

Chapter:
(p.192) 6 LEAST SQUARES INVERSE EIGENVALUE PROBLEMS
Source:
Inverse Eigenvalue Problems
Author(s):

Moody T. Chu

Gene H. Golub

Publisher:
Oxford University Press
DOI:10.1093/acprof:oso/9780198566649.003.0006

Every inverse eigenvalue problem has a natural generalization to a least squares formulation, which sometimes does carry significant purposes in applications. The least squares approximation can be applied to either the spectral constraint or the structural constraint. This chapter highlights some of the main notions when considering a least squares inverse problem, and describes a hybrid lift and projection method.

Keywords:   eigenvalue problem, least squares, lift and projection, hybrid methods

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