Impact of source model matrix conditioning on iterative PEVD algorithms

J Corr, K Thompson, S Weiss, I K Proudler, J G McWhirter

Research output: Contribution to conferencePaper

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Abstract

Polynomial parahermitian matrices can accurately and elegantly capture the space-time covariance in broadband array problems. To factorise such matrices, a number of polynomial EVD (PEVD) algorithms have been suggested. At every step, these algorithms move various amounts of off-diagonal energy onto the diagonal, to eventually reach an approximate diagonalisation. In practical experiments, we have found that the relative performance of these algorithms depends quite significantly on the type of parahermitian matrix that is to be factorised. This paper aims to explore this performance space, and to provide some insight into the characteristics of PEVD algorithms.
Original languageEnglish
DOIs
Publication statusPublished - 1 Dec 2015
Event2nd IET International Conference on Intelligent Signal Processing - Kensington Close Hotel, London, United Kingdom
Duration: 1 Dec 20152 Dec 2015

Conference

Conference2nd IET International Conference on Intelligent Signal Processing
CountryUnited Kingdom
CityLondon
Period1/12/152/12/15

Keywords

  • polynomial eigenvalue decomposition
  • broadband array processing
  • space-time covariance matrix
  • polynomial matrix
  • matrix factorisation
  • eigenvalues and eigenfunctions
  • PEVD algorithms

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