Computing the nearest circulant positive semi-definite matrix to a noisy matrix

Suliman Al-Homidan*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

This paper construct structured circulant positive semi-definite matrix that is nearest to a given data matrix. The problem arises in various applications where the data collected in a matrix do not maintain either the specified structure or the desirable rank as is expected in the original system. The task is to retrieve useful information while maintaining the underlying physical feasibility often necessitates search for a good structured approximation of the data matrix. We presented new methods to determine approximation of optimal matrices. Comparative numerical results are also reported.

Original languageEnglish
Pages (from-to)309-319
Number of pages11
JournalJournal of Nonlinear and Convex Analysis
Volume22
Issue number2
StatePublished - 2021

Bibliographical note

Publisher Copyright:
© 2021 Yokohama Publications. All rights reserved.

Keywords

  • Alternating projections
  • Circulant matrix
  • Hybrid methods
  • Non-smooth optimization
  • Permutative matrix
  • Positive semi-definite matrix
  • SQP method

ASJC Scopus subject areas

  • Analysis
  • Geometry and Topology
  • Control and Optimization
  • Applied Mathematics

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