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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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STRUCTURED LOW RANK APPROXIMATION

STRUCTURED LOW RANK APPROXIMATION

Chapter:
(p.246) 8 STRUCTURED LOW RANK APPROXIMATION
Source:
Inverse Eigenvalue Problems
Author(s):

Moody T. Chu

Gene H. Golub

Publisher:
Oxford University Press
DOI:10.1093/acprof:oso/9780198566649.003.0008

The task of retrieving useful information while maintaining the underlying physical feasibility often necessitates the search for a good structured lower rank approximation of the data matrix. This chapter addresses some of the theoretical and numerical issues involved in this kind of problem. Six different structures representing different flavors of structures are considered: Toeplitz, circulant, covariance, Euclidean distance, normalized data, and nonnegative matrices.

Keywords:   structured problems, Toeplitz, circulant, covariance, Euclidean distance, nonnegative matrices

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