Multiple shift, maximum element sequential matrix diagonalisation for parahermitian matrices

Corr, Jamie, Thompson, Keith, Weiss, Stephan, McWhirter, John ORCID: https://orcid.org/0000-0003-1810-3318, Redif, Soydan and Proudler, Ian K. 2014. Multiple shift, maximum element sequential matrix diagonalisation for parahermitian matrices. Presented at: 2014 IEEE Workshop on Statistical Signal Processing (SSP), Gold Coast, Australia, June 29 -July 2 2014. Statistical Signal Processing (SSP), 2014 IEEE Workshop on. Proc IEEE 8th Sensor Array and Multichannel Signal Processing Workshop. IEEE, pp. 312-315. 10.1109/SSP.2014.6884638

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Abstract

A polynomial eigenvalue decomposition of paraher- mitian matrices can be calculated approximately using iterative approaches such as the sequential matrix diagonalisation (SMD) algorithm. In this paper, we present an improved SMD algorithm which, compared to existing SMD approaches, eliminates more off-diagonal energy per step. This leads to faster convergence while incurring only a marginal increase in complexity. We motivate the approach, prove its convergence, and demonstrate some results that underline the algorithm’s performance.

Item Type:	Conference or Workshop Item (Paper)
Date Type:	Publication
Status:	Published
Schools:	Engineering
Publisher:	IEEE
Funders:	EPSRC, MOD University Defence Research Collaboration in Signal Processing
Related URLs:	http://ieeexplore.ieee.org/xpl/abstractA...
Date of First Compliant Deposit:	30 March 2016
Last Modified:	06 Nov 2023 21:37
URI:	https://orca.cardiff.ac.uk/id/eprint/69087

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