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ICA by Mutual Information minimization: An approach for avoiding local minima

Babaie Zadeh, M ; Sharif University of Technology | 2005

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  1. Type of Document: Article
  2. Publisher: 2005
  3. Abstract:
  4. Using Mutual Information (MI) minimization is very common in Blind Source Separation (BSS). However, it is known that gradient descent approaches may trap in local minima of MI in constrained models. In this paper, it is proposed that this problem may be solved using a 'poor' estimation of the derivative of MI
  5. Keywords:
  6. Constrained models ; Gradient descent ; Local minimums ; Mutual informations ; Signal processing ; Blind source separation
  7. Source: 13th European Signal Processing Conference, EUSIPCO 2005, Antalya, 4 September 2005 through 8 September 2005 ; 2005 , Pages 253-256 ; 1604238216 (ISBN); 9781604238211 (ISBN)
  8. URL: https://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.134.4397&rep=rep1&type=pdf