| Paper: | MLSP-P5.7 | ||
| Session: | Blind Source Separation III | ||
| Time: | Friday, May 19, 14:00 - 16:00 | ||
| Presentation: | Poster | ||
| Topic: | Machine Learning for Signal Processing: Blind Signal Separation and Independent Component Analysis | ||
| Title: | A time-frequency correlation-based blind source separation method for time-delayed mixtures | ||
| Authors: | Matthieu Puigt, Yannick Deville, Laboratoire d'Astrophysique de Toulouse-Tarbes, France | ||
| Abstract: | We propose a time-frequency (TF) blind source separation (BSS) method suited to attenuated and delayed (AD) mixtures, inspired from a method that we previously developed for linear instantaneous mixtures. This approach only requires each of the uncorrelated sources to occur alone in a tiny TF zone, i.e. it sets very limited constraints on the source sparsity and overlap, unlike various previously reported TF-BSS methods. Our approach is based on TIme-Frequency CORRelation (hence its name AD-TIFCORR). It consists in identifying the columns of the (filtered permuted) mixing matrix in TF zones where it detects that a single source occurs. We thus identify columns of scale coefficients and time shifts. This method is especially suited to non-stationary sources. | ||
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