Multichannel identification of room acoustic systems with adaptive filters based on orthonormal basis functions

Giacomo Vairetti, Soren Holdt Jensen, Enzo De Sena, Marc Moonen, Michael Catrysse, Toon van Waterschoot

Research output: Contribution to book/anthology/report/conference proceedingArticle in proceedingResearchpeer-review

5 Citations (Scopus)

Abstract

Many acoustic signal enhancement applications require adaptive filters with a long impulse response, but with a small number of filter parameters. Fixed-poles infinite impulse response (IIR) adaptive filters based on orthonormal basis functions (OBFs) present advantages over finite impulse response filters and other IIR filters, assuring stability and fast global convergence in the adaptation of the filter parameters. A scalable algorithm is introduced for the estimation of the poles of an adaptive OBF filter from multichannel input-output data. The set of poles, common to all the acoustic channels considered, is estimated in parallel to the adaptation of the linear filter parameters. It will be shown that the result of the identification with common poles is quite robust to variations in the room transfer function, suggesting the possibility that poles may be kept fixed after estimation.

Original languageEnglish
Title of host publication2016 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2016 - Proceedings
Number of pages5
PublisherIEEE
Publication date18 May 2016
Pages16-20
Article number7471628
ISBN (Electronic)9781479999880
DOIs
Publication statusPublished - 18 May 2016
Event41st IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2016 - Shanghai, China
Duration: 20 Mar 201625 Mar 2016

Conference

Conference41st IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2016
Country/TerritoryChina
CityShanghai
Period20/03/201625/03/2016
SponsorThe Institute of Electrical and Electronics Engineers Signal Processing Society

Keywords

  • adaptive filtering
  • identification
  • Orthonormal basis functions
  • parametric modeling
  • room acoustics

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