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Blind source separation algorithm based on wavelet denoising

  • Xin Liu*
  • , Xue Zhi Tan
  • , Shou Ming Wei
  • , Anna Auguste Anghuwo
  • *Corresponding author for this work
  • Harbin Institute of Technology

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

Abstract

In this paper, a method of blind source separation (BSS) is proposed based on wavelet denoising. This method firstly makes wavelet transform (WT) to the observation signals, and then adopts a uniform method which combines signal whitening and maximum information algorithm to obtain the separate signals which approach to the source signals. Simulations show this method could achieve better performance than that without wavelet denoising, and when the iterative number reaches 4000, it could achieve very good results.

Original languageEnglish
Title of host publicationProceedings - 2010 1st International Conference on Pervasive Computing, Signal Processing and Applications, PCSPA 2010
Pages739-742
Number of pages4
DOIs
StatePublished - 2010
Event1st International Conference on Pervasive Computing, Signal Processing and Applications, PCSPA 2010 - Harbin, China
Duration: 17 Sep 201019 Sep 2010

Publication series

NameProceedings - 2010 1st International Conference on Pervasive Computing, Signal Processing and Applications, PCSPA 2010

Conference

Conference1st International Conference on Pervasive Computing, Signal Processing and Applications, PCSPA 2010
Country/TerritoryChina
CityHarbin
Period17/09/1019/09/10

Keywords

  • Blind source separation
  • Signal whitening
  • Wavelet denoising
  • Wavelet transform

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