Impact of source model matrix conditioning on PEVD algorithms
Impact of source model matrix conditioning on PEVD algorithms
- Author(s): J. Corr ; K. Thompson ; S. Weiss ; I.K. Proudler ; J.G. McWhirter
- DOI: 10.1049/cp.2015.1771
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- Author(s): J. Corr ; K. Thompson ; S. Weiss ; I.K. Proudler ; J.G. McWhirter Source: 2nd IET International Conference on Intelligent Signal Processing 2015 (ISP), 2015 page ()
- Conference: 2nd IET International Conference on Intelligent Signal Processing 2015 (ISP)
- DOI: 10.1049/cp.2015.1771
- ISBN: 978-1-78561-136-0
- Location: London, UK
- Conference date: 1-2 Dec. 2015
- Format: PDF
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.
Inspec keywords: polynomial matrices; eigenvalues and eigenfunctions
Subjects: Algebra; Algebra; Algebra, set theory, and graph theory; Algebra
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