Journal of Guangdong University of Technology ›› 2008, Vol. 25 ›› Issue (4): 61-64.

• Comprehensive Studies • Previous Articles     Next Articles

Underdetermined Blind Source Separation Based on Locally Sparse Representations

  

  1. 1.Faculty of Applied Mathematics,Guangdong University of Technology,Guangzhou 510006,China;2.Faculty of Information Engineering,JiangXi University of Science and Technology,Ganzhou 341000
  • Online:2008-03-01 Published:2008-03-01

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Abstract: It proposes a new algorithm of locally sparse blind source separation for estimating the mixed matrix A.This method doesn’t require all the samples of the sources are strictly sparse.Firstly all the vectors in the same line were searched for and classified.And then the mixed matrix A determined.The simulation illustrates the effectiveness of this algorithrn.

Key words: blind seurce separation； sparse； strictly sparse； underdetermined；

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