| 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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