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Memory and complexity reduction in parahermitian matrix manipulations of PEVD algorithms

Coutts, Fraser K., Corr, Jamie, Thompson, Keith, Weiss, Stephan, Proudler, Ian K. and McWhirter, John 2016. Memory and complexity reduction in parahermitian matrix manipulations of PEVD algorithms. Presented at: 2016 24th European Signal Processing Conference (EUSIPCO), 29 August - 2 September 2016. 2016 24th European Signal Processing Conference (EUSIPCO). Piscataway, NJ: IEEE, pp. 1633-1637. 10.1109/EUSIPCO.2016.7760525

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Abstract

A number of algorithms for the iterative calculation of a polynomial matrix eigenvalue decomposition (PEVD) have been introduced. The PEVD is a generalisation of the ordinary EVD and will diagonalise a parahermitian matrix via paraunitary operations. This paper addresses savings - both computationally and in terms of memory use - that exploit the parahermitian structure of the matrix being decomposed, and also suggests an implicit trimming approach to efficiently curb the polynomial order growth usually observed during iterations of the PEVD algorithms. We demonstrate that with the proposed techniques, both storage and computations can be significantly reduced, impacting on a number of broadband multichannel problems.

Item Type: Conference or Workshop Item (Paper)
Date Type: Publication
Status: Published
Schools: Engineering
Publisher: IEEE
ISBN: 978-0-9928-6265-7
ISSN: 2076-1465
Last Modified: 04 Jul 2019 13:13
URI: http://orca.cf.ac.uk/id/eprint/99091

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