Polynomial eigenvalue decomposition for multichannel broadband signal processing
File(s)2023-08-spm.pdf (3.57 MB)
Accepted version
Author(s)
Type
Journal Article
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.
Date Issued
2023-11-01
Date Acceptance
2023-04-04
Citation
IEEE: Signal Processing Magazine, 2023, 40 (7), pp.18-37
ISSN
1053-5888
Publisher
Institute of Electrical and Electronics Engineers
Start Page
18
End Page
37
Journal / Book Title
IEEE: Signal Processing Magazine
Volume
40
Issue
7
Copyright Statement
Copyright This paper is embargoed until publication. Copyright © 2023 IEEE. © 2023 IEEE. Personal use is permitted, but republication/redistribution requires IEEE permission. The author has applied a ’Creative Commons Attribution’ (CC BY) licence to any Author Accepted Manuscript version arising.
License URL
Publication Status
Published
Date Publish Online
2023-12-31