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Sequential matrix diagonalisation algorithms for polynomial EVD of parahermitian matrices

Redif, Soydan, Weiss, Stephan and McWhirter, John 2015. Sequential matrix diagonalisation algorithms for polynomial EVD of parahermitian matrices. IEEE Transactions on Signal Processing 63 (1) , pp. 81-89. 10.1109/tsp.2014.2367460

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Abstract

For parahermitian polynomial matrices, which can be used, for example, to characterise space-time covariance in broadband array processing, the conventional eigenvalue decomposition (EVD) can be generalised to a polynomial matrix EVD (PEVD). In this paper, a new iterative PEVD algorithm based on sequential matrix diagonalisation (SMD) is introduced. At every step the SMD algorithm shifts the dominant column or row of the polynomial matrix to the zero lag position and eliminates the resulting instantaneous correlation. A proof of convergence is provided, and it is demonstrated that SMD establishes diagonalisation faster and with lower order operations than existing PEVD algorithms.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Engineering
Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering
Publisher: Institute of Electrical and Electronics Engineers
ISSN: 1053-587X
Date of First Compliant Deposit: 30 March 2016
Date of Acceptance: 2014
Last Modified: 02 Aug 2017 15:05
URI: http://orca.cf.ac.uk/id/eprint/68978

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