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| 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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