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