Polynomial eigenvalue decomposition for multichannel broadband signal processing : a mathematical technique offering new insights and solutions

Neo, Vincent W. and Redif, Soydan and McWhirter, John G. and Pestana, Jennifer and Proudler, Ian K. and Weiss, Stephan and Naylor, Patrick A. (2023) Polynomial eigenvalue decomposition for multichannel broadband signal processing : a mathematical technique offering new insights and solutions. IEEE Signal Processing Magazine, 40 (7). pp. 18-37. ISSN 1053-5888 (https://doi.org/10.1109/MSP.2023.3269200)

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Abstract

This article is devoted to the polynomial eigenvalue decomposition (PEVD) and its applications in broadband multichannel signal processing, motivated by the optimum solutions provided by the EVD for the narrowband case [1], [2]. In general, we would like to extend the utility of the EVD to also address broadband problems. Multichannel broadband signals arise at the core of many essential commercial applications, such as telecommunications, speech processing, health-care monitoring, astronomy and seismic surveillance, and military technologies, including radar, sonar, and communications [3]. The success of these applications often depends on the performance of signal processing tasks, including data compression [4], source localization [5], channel coding [6], signal enhancement [7], beamforming [8], and source separation [9]. In most cases and for narrowband signals, performing an EVD is the key to the signal processing algorithm. Therefore, this article aims to introduce the PEVD as a novel mathematical technique suitable for many broadband signal processing applications.

ORCID iDs

Neo, Vincent W., Redif, Soydan, McWhirter, John G., Pestana, Jennifer ORCID logoORCID: https://orcid.org/0000-0003-1527-3178, Proudler, Ian K., Weiss, Stephan ORCID logoORCID: https://orcid.org/0000-0002-3486-7206 and Naylor, Patrick A.;

Persistent Identifier

https://doi.org/10.17868/strath.00085117
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