DocumentCode :
79776
Title :
Successive Projection Method for Well-Conditioned Matrix Approximation Problems
Author :
Tanaka, Mitsuru ; Nakata, K.
Author_Institution :
Dept. of Ind. Eng. & Manage., Tokyo Inst. of Technol., Tokyo, Japan
Volume :
21
Issue :
4
fYear :
2014
fDate :
Apr-14
Firstpage :
418
Lastpage :
422
Abstract :
Matrices are often required to be well-conditioned in a wide variety of areas including signal processing. Problems to find the nearest positive definite matrix or the nearest correlation matrix that simultaneously satisfy the condition number constraint and sign constraints are presented in this paper. Both problems can be regarded as those to find a projection to the intersection of the closed convex cone corresponding to the condition number constraint and the convex polyhedron corresponding to the other constraints. Thus, we can apply a successive projection method, which is a classical algorithm for finding the projection to the intersection of multiple convex sets, to these problems. The numerical results demonstrated that the algorithm effectively solved the problems.
Keywords :
matrix algebra; signal processing; closed convex cone; condition number constraint; convex polyhedron; convex set intersection; nearest correlation matrix; positive definite matrix; sign constraint; signal processing; successive projection method; well-conditioned matrix approximation problem; Approximation algorithms; Correlation; Covariance matrices; Least squares approximations; Signal processing algorithms; Symmetric matrices; Tin; Covariance matrices; estimation; iterative algorithms; least squares approximations;
fLanguage :
English
Journal_Title :
Signal Processing Letters, IEEE
Publisher :
ieee
ISSN :
1070-9908
Type :
jour
DOI :
10.1109/LSP.2014.2303153
Filename :
6727420
Link To Document :
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