Nonlinear single channel source separation

A. M. Darsono, Bin Gao, W. L. Woo, S. S. Dlay

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

4 Citations (Scopus)

Abstract

A new model of nonlinear single channel source separation is proposed in this paper. The proposed model is a linear mixture of the independent sources followed by an element-wise post-nonlinear distortion function. In addition, the paper develops a novel solution that efficiently compensates for the nonlinear distortion and performs source separation. The proposed solution is a two-stage process that consists of a Gaussianization transform and a maximum likelihood estimator for the sources. The paper also discusses the theory behind the proposed solution. Simulations have been carried out to verify the theory and evaluate the performance of the proposed algorithm. Results obtained have shown the effectiveness of the algorithm even in presence of the strong nonlinearity.

Original languageEnglish
Title of host publication2010 7th International Symposium on Communication Systems, Networks and Digital Signal Processing, CSNDSP 2010
PublisherIEEE
Pages507-511
Number of pages5
ISBN (Electronic)9781861353696
ISBN (Print)9781424488582
Publication statusPublished - 20 Sept 2010
Event2010 7th International Symposium on Communication Systems, Networks and Digital Signal Processing, CSNDSP 2010 - Newcastle upon Tyne, United Kingdom
Duration: 21 Jul 201023 Jul 2010

Conference

Conference2010 7th International Symposium on Communication Systems, Networks and Digital Signal Processing, CSNDSP 2010
Country/TerritoryUnited Kingdom
CityNewcastle upon Tyne
Period21/07/1023/07/10

Keywords

  • Blind source separation
  • Gaussianization transform and maximum likelihood
  • Independent component analysis

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