Vincent W. Neo;Soydan Redif;John G. McWhirter;Jennifer Pestana;Ian K. Proudler;Stephan Weiss;Patrick A. Naylor
{"title":"Polynomial Eigenvalue Decomposition for Multichannel Broadband Signal Processing: A mathematical technique offering new insights and solutions","authors":"Vincent W. Neo;Soydan Redif;John G. McWhirter;Jennifer Pestana;Ian K. Proudler;Stephan Weiss;Patrick A. Naylor","doi":"10.1109/MSP.2023.3269200","DOIUrl":null,"url":null,"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 \n<xref>[1]</xref>\n, \n<xref>[2]</xref>\n. 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 \n<xref>[3]</xref>\n. The success of these applications often depends on the performance of signal processing tasks, including data compression \n<xref>[4]</xref>\n, source localization \n<xref>[5]</xref>\n, channel coding \n<xref>[6]</xref>\n, signal enhancement \n<xref>[7]</xref>\n, beamforming \n<xref>[8]</xref>\n, and source separation \n<xref>[9]</xref>\n. 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.","PeriodicalId":13246,"journal":{"name":"IEEE Signal Processing Magazine","volume":null,"pages":null},"PeriodicalIF":9.4000,"publicationDate":"2023-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Signal Processing Magazine","FirstCategoryId":"5","ListUrlMain":"https://ieeexplore.ieee.org/document/10313230/","RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
引用次数: 1
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.
期刊介绍:
EEE Signal Processing Magazine is a publication that focuses on signal processing research and applications. It publishes tutorial-style articles, columns, and forums that cover a wide range of topics related to signal processing. The magazine aims to provide the research, educational, and professional communities with the latest technical developments, issues, and events in the field. It serves as the main communication platform for the society, addressing important matters that concern all members.