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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.
|Number of pages||6|
|Publication status||Published - 3 Oct 2017|
|Event||IEEE International Workshop on Signal Processing Systems - Lorient, France|
Duration: 3 Oct 2017 → 5 Oct 2017
|Conference||IEEE International Workshop on Signal Processing Systems|
|Abbreviated title||SiPS 2017|
|Period||3/10/17 → 5/10/17|
- polynomial matrix eigenvalue decomposition
- sensor arrays
- PEVD algorithms
- signal processing
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Soraghan, J. & Weiss, S.
1/04/13 → 31/03/18