Analysing the performance of divide-and-conquer sequential matrix diagonalisation for large broadband sensor arrays

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Coutts, Fraser K. and Thompson, Keith and Weiss, Stephan and Proudler, Ian K. (2017) Analysing the performance of divide-and-conquer sequential matrix diagonalisation for large broadband sensor arrays. In: IEEE International Workshop on Signal Processing Systems, 2017-10-03 - 2017-10-05. (https://doi.org/10.1109/SiPS.2017.8109976)

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Abstract

A number of algorithms capable of iteratively calculating a polynomial matrix eigenvalue decomposition (PEVD) have been introduced. The PEVD is an extension of the ordinary EVD to polynomial matrices and will diagonalise a parahermitian matrix using paraunitary operations. Inspired by recent work towards a low complexity divide-and-conquer PEVD algorithm, this paper analyses the performance of this algorithm - named divide-and-conquer sequential matrix diagonalisation (DC-SMD) - for applications involving broadband sensor arrays of various dimensionalities. We demonstrate that by using the DC-SMD algorithm instead of a traditional alternative, PEVD complexity and execution time can be significantly reduced. This reduction is shown to be especially impactful for broadband multichannel problems involving large arrays.

ORCID iDs

Coutts, Fraser K. ORCID logoORCID: https://orcid.org/0000-0003-2299-2648, Thompson, Keith ORCID logoORCID: https://orcid.org/0000-0003-0727-7347, Weiss, Stephan ORCID logoORCID: https://orcid.org/0000-0002-3486-7206 and Proudler, Ian K.;
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