A parallel processed scheme for the eigenproblem of positive definite matrices

M. A. Shalaby*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

This paper deals with the eigenproblem of positive definite matrices. A numerical algorithm, to find the largest eigenvalues of a full positive definite matrix using Householder reflections, is described. The proposed algorithm can be used to find all the eigenvalues of a symmetric matrix or at least the first few largest ones. The scheme is proved to be convergent and the convergence rate is calculated. The full matrix is operated upon, at each iteration; hence one could use the APL programming language to write down a very brief code to implement the program.

Original languageEnglish (US)
Pages (from-to)99-106
Number of pages8
JournalJournal of Computational and Applied Mathematics
Volume54
Issue number1
DOIs
StatePublished - Sep 20 1994

Keywords

  • Eigenvalues
  • Parallel processing

ASJC Scopus subject areas

  • Computational Mathematics
  • Applied Mathematics

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