Investigation of a polynomial matrix generalised EVD for multi-channel Wiener filtering

Jamie Corr, Jennifer Pestana, Stephan Weiss, Soydan Redif, Marc Moonen

Research output: Chapter in Book/Report/Conference proceedingConference contribution book

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Abstract

State of the art narrowband noise cancellation techniques utilise the generalised eigenvalue decomposition (GEVD) for multichannel Wiener filtering which can be applied to independent frequency bins in order to achieve broadband processing. Here we investigate the extension of the GEVD to broadband, polynomial matrices, akin to strategies that have already been developed by McWhirter et. al on the polynomial matrix eigenvalue decomposition (PEVD).
Original languageEnglish
Title of host publication50th Asilomar Conference on Signals, Systems and Computers
PublisherIEEE
Publication statusAccepted/In press - 19 Jul 2016
Event50th Asilomar Conference on Signals, Systems and Computers - Asilomar Conference Ground, Pacific Grove, CA, United States
Duration: 6 Nov 20169 Nov 2016
http://www.asilomarsscconf.org/

Conference

Conference50th Asilomar Conference on Signals, Systems and Computers
Abbreviated titleAsilomar 2016
CountryUnited States
CityPacific Grove, CA
Period6/11/169/11/16
Internet address

Keywords

  • narrowband noise cancellation techniques
  • generalised eigenvalue decomposition
  • multichannel Wiener filtering
  • independent frequency bins
  • polynomial matrices
  • polynomial matrix eigenvalue decomposition

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    Corr, J., Pestana, J., Weiss, S., Redif, S., & Moonen, M. (Accepted/In press). Investigation of a polynomial matrix generalised EVD for multi-channel Wiener filtering. In 50th Asilomar Conference on Signals, Systems and Computers IEEE.