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Overdetermined Blind Source Separation by Gaussian Mixture Model

  • Yujia Wang
  • Yunfeng Xue
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6839)

Abstract

The blind separation of overdetermined mixtures, i.e., the case where more sensors than sources are available is considered in this paper. The contrast function for overdetermined blind source separation problem is presented, together with its gradient. An iterative method is proposed to solve the overdetermined blind source separation problem, where Gaussian mixture model is used to estimate the density of the unknown sources. The result of simulation demonstrates the efficiency of the proposed algorithm.

Keywords

Gaussian Mixture Model Independent Component Analysis Blind Source Separation Blind Signal Gradient Descent Method 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Yujia Wang
    • 1
  • Yunfeng Xue
    • 2
  1. 1.Department of AutomationShanghai University of Engineering SciencePR China
  2. 2.School of Electronic and Electrical EngineeringShanghai Second Polytechnic UniversityPR China

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