Polynomial eigenvalue decomposition for multichannel broadband signal processing

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. IEEE Signal Processing Magazine. ISSN 1053-5888 (In Press)

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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 eigenvalue decomposition (EVD) for the narrow-band case [1], [2]. In general, the successful techniques from narrowband problems can also be applied to broadband ones, leading to improved solutions. Multichannel broadband signals arise at the core of many essential commercial applications such as telecommunications, speech processing, healthcare monitoring, astronomy and seismic surveillance, and military technologies like 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 paper aims to introduce 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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