Blind extraction of noisy events using nonlinear predictor

Wai Yie Leong, Danilo P. Mandic, Wei Liu

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

12 Citations (Scopus)

Abstract

Existing blind source extraction (BSE) methods are limited to noise-free mixtures, which is not realistic. We therefore address this issue and propose an algorithm based on the normalised kurtosis and a nonlinear predictor within the BSE structure, which makes this class of algorithms suitable for noisy environments, a typical situation in practice. Based on a rigorous analysis of the existing BSE methods we also propose a new optimisation paradigm which aims at minimising the normalised mean square prediction error (MSPE). This makes redundant the need for preprocessing or orthogonality transform. Simulation results are provided which confirm the validity of the theoretical results and demonstrate the performance of the derived algorithms in noisy mixing environments.

Original languageEnglish
Title of host publication2007 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP '07
PagesII657-II660
DOIs
Publication statusPublished - Jun 2007
Event2007 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP '07 - Honolulu, HI, United States
Duration: 15 Apr 200720 Apr 2007

Publication series

NameICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Volume2
ISSN (Print)1520-6149

Conference

Conference2007 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP '07
Country/TerritoryUnited States
CityHonolulu, HI
Period15/04/0720/04/07

Keywords

  • Adaptive nonlinear prediction
  • Blind source extraction
  • Blind source separation
  • Noisy mixtures

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering

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