Performance analysis of over-determined noisy ICA: Bayesian approach versus signal transformation

Yuanjia Wu*, W. L. Woo, S. S. Dlay

*Corresponding author for this work

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

Abstract

This paper proposes a new analysis on two robust methods for solving the blind source separation problem of noisy linear over-determined mixtures using 2-Stage ICA and Bayesian approach. A new method has also been developed to determine the optimal SNR threshold as the selection index for choosing the better method under the varying influence of the noise levels. An experimental simulation has been analytically conducted to verify the proposed method. An in-depth analysis has been carried out between the two methods regarding to their different performances through out the noise level from -10dB to 30dB. It is further shown that the threshold selection can be generalized to more complex cases that have the same ratio between the number of observed signals and the number of sources.

Original languageEnglish
Title of host publicationProceedings of the 6th International Symposium Communication Systems, Networks and Digital Signal Processing, CSNDSP 08
PublisherIEEE
Pages147-151
Number of pages5
ISBN (Print)9781424418756
DOIs
Publication statusPublished - 29 Aug 2008
Event6th International Symposium Communication Systems, Networks and Digital Signal Processing, CSNDSP 08 - Graz, Austria
Duration: 23 Jul 200825 Jul 2008

Conference

Conference6th International Symposium Communication Systems, Networks and Digital Signal Processing, CSNDSP 08
Country/TerritoryAustria
CityGraz
Period23/07/0825/07/08

Keywords

  • Bayesian analysis
  • Blind source separation
  • Extended ICA
  • Independent component analysis
  • Over-determined

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