On the algorithmization of janashia-lagvilava matrix spectral factorization method

Lasha Ephremidze, Faisal Saied, Ilya Spitkovsky

Research output: Contribution to journalArticle

Abstract

We consider three different ways of algorithmization of the Janashia-Lagvilava spectral factorization method. The first algorithm is faster than the second one, however, it is only suitable for matrices of low dimension. The second algorithm, on the other hand, can be applied to matrices of substantially larger dimension. The third algorithm is a superfast implementation of the method, but only works in the polynomial case under the additional restriction that the zeros of the determinant are not too close to the boundary. All three algorithms fully utilize the advantage of the method, which carries out spectral factorization of leading principal submatrices step-by-step. The corresponding results of numerical simulations are reported in order to describe the characteristic features of each algorithm and compare them to other existing algorithms.

Original languageEnglish (US)
Article number8105834
Pages (from-to)728-737
Number of pages10
JournalIEEE Transactions on Information Theory
Volume64
Issue number2
DOIs
StatePublished - Feb 1 2018

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Factorization
Polynomials
determinants
simulation
Computer simulation

Keywords

  • Algorithms
  • Spectral factorization

ASJC Scopus subject areas

  • Information Systems
  • Computer Science Applications
  • Library and Information Sciences

Cite this

On the algorithmization of janashia-lagvilava matrix spectral factorization method. / Ephremidze, Lasha; Saied, Faisal; Spitkovsky, Ilya.

In: IEEE Transactions on Information Theory, Vol. 64, No. 2, 8105834, 01.02.2018, p. 728-737.

Research output: Contribution to journalArticle

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