Technical Program

Paper Detail

Paper:MLSP-P1.3
Session:Blind Source Separation and ICA
Time:Tuesday, May 18, 15:30 - 17:30
Presentation: Poster
Topic: Machine Learning for Signal Processing: Blind Signal Separation and Independent Component Analysis
Title: A MINIMIZATION-PROJECTION (MP) APPROACH FOR BLIND SEPARATING CONVOLUTIVE MIXTURES
Authors: Massoud Babaie-Zadeh; Sharif University of Technology 
 Christian Jutten; Institut National Polytechnique de Grenoble (INPG) 
 Kambiz Nayebi; Sharif University of Technology 
Abstract: In this paper, a new algorithm for blind source separation inconvolutive mixtures, based on minimizing the mutual informationof the outputs, is proposed. This minimization is done using arecently proposed Minimization-Projection (MP) approach forminimizing mutual information in a parametric model. Since theminimization step of the MP approach is proved to have no localminimum, it is expected that this new algorithm has goodconvergence behaviours.
 
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