Generalized combined nonlinear adaptive filters for nonlinear acoustic echo cancellation

Wenxia Lu, Lijun Zhang, Jie Chen, Jingdong Chen

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

This paper proposes a new and generalized algorithm of combination of nonlinear adaptive filters (CNAF) for nonlinear acoustic echo cancellation (NAEC). In contrast to combining filters in a conventional parallel manner, the candidate filters are organized to form in a network structure with two subnetworks. The nodes in each subnetwork serve as linear and nonlinear adaptive filters respectively. A generalized CNAF (GCNAF) is then obtained by linking the nodes in the network and using the diffusion adaptation strategy. The proposed GCNAF algorithm allows information exchange and sharing among the nodes, so as to maximally optimize the performance of the combined filters. Simulations with noise and speech signals demonstrate the effectiveness of the proposed GCNAF for the NAEC problem.

Original languageEnglish
Title of host publication2019 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1220-1225
Number of pages6
ISBN (Electronic)9781728132488
DOIs
StatePublished - Nov 2019
Event2019 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2019 - Lanzhou, China
Duration: 18 Nov 201921 Nov 2019

Publication series

Name2019 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2019

Conference

Conference2019 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2019
Country/TerritoryChina
CityLanzhou
Period18/11/1921/11/19

Keywords

  • Distributed optimization
  • Generalized combination of nonlinear adaptive filters
  • Nonlinear acoustic echo cancellation

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