• 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