Journal of South China University of Technology (Natural Science Edition) ›› 2010, Vol. 38 ›› Issue (6): 19-23.doi: 10.3969/j.issn.1000-565X.2010.06.004

• Electronics, Communication & Automation Technology • Previous Articles     Next Articles

Underdetermined and Incompletely-Sparse Blind Source Recovery

Zhao Min1  Xie Sheng-li1  Xiao Ming2   

  1. 1.School of Electronic and Information Engineering,South China University of Technology,Guangzhou 510640,Guangdong,China;2.Department of Electrics and Information Engineering,Guangdong University of Petrochemical Technology,Maoming 525000,Guangdong,China
  • Received:2009-09-03 Revised:2009-10-13 Online:2010-06-25 Published:2010-06-25
  • Contact: 赵敏（1970-），男，博士生，主要从事盲信号分离研究． E-mail:adzhaom@scut．edu．cn
  • About author:赵敏（1970-），男，博士生，主要从事盲信号分离研究．
  • Supported by:

    国家“973”计划项目（2010CB731800）; 国家自然科学基金资助项目（60774094 60874061）; 国家自然科学基金重点项目（U0635001 U0835003）

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Abstract:

As the existing algorithms of blind source separation（BSS） are suitable only for sparse sources but not for incompletely-sparse sources,a statistically non-sparse decomposition principle（SNSDP） is proposed for two observed signals.In this algorithm,the signals are divided into several intervals and the incomplete sparsity of the intervals is determined according to the correlativity of the sources.By utilizing different source recovery strategies for both the sparse and the incompletely-sparse intervals,the estimated sources can be improved.Simulated results indicate that,as compared with the traditional algorithms,the proposed algorithm greatly improves the waveforms of recovered signals and increases the signal-to-interference ratio.

Key words: blind source separation, underdetermination, sparse representation, incomplete sparsity