An Novel Algorithm for Blind Source Separation with Unknown Sources Number

  • Ji-Min Ye
  • Shun-Tian Lou
  • Hai-Hong Jin
  • Xian-Da Zhang
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3971)


The natural gradient blind source separation (BSS) algorithm with unknown source number proposed by Cichocki in 1999 is justified in this paper. An new method to detect the redundant separated signals based on structure of separating matrix is proposed, by embedding it into the natural gradient algorithm, an novel BSS algorithm with an unknown source number is developed. The novel algorithm can successfully separate source signals and converge stably, while the Cichocki’s algorithm would diverge inevitably. The new method embedded in novel algorithm can detect and cancel the redundant separated signals within 320 iteration, which is far quicker than the method based on the decorrelation, if some parameters are chosen properly.


Mutual Information Independent Component Analysis Blind Source Separation Neural Computation Natural Gradient 
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 2006

Authors and Affiliations

  • Ji-Min Ye
    • 1
  • Shun-Tian Lou
    • 1
  • Hai-Hong Jin
    • 2
  • Xian-Da Zhang
    • 3
  1. 1.Key Lab for Radar Signal ProcessingXidian UniversityXi’anChina
  2. 2.School of ScienceXi’an Petroleum UniversityXi’anChina
  3. 3.Department of Automation, State Key Lab of Intelligent Technology and SystemsTsinghua UniversityBeijingChina

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