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

Vincent W. Neo, Soydan Redif, John G. McWhirter, Jennifer Pestana, Ian K. Proudler, Stephan Weiss, Patrick A. Naylor

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)
126 Downloads (Pure)

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.

Original languageEnglish
Pages (from-to)18-37
Number of pages20
JournalIEEE Signal Processing Magazine
Volume40
Issue number7
DOIs
Publication statusPublished - 8 Nov 2023

Keywords

  • polynomial matrix
  • polynomial matrix eigen value decomposition
  • multichannel broadband processing
  • space-time covariance matrix
  • lossless filter banks
  • broadband beamforming
  • subband coding
  • speech enchancement

Fingerprint

Dive into the research topics of 'Polynomial eigenvalue decomposition for multichannel broadband signal processing: a mathematical technique offering new insights and solutions'. Together they form a unique fingerprint.

Cite this