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Blind identification and separation methods for Linear-Quadratic mixtures and/or linearly independent non-stationary signals

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2 Author(s)
Yannick Deville ; Université Paul Sabatier Toulouse 3 - Observatoire Midi-Pyrénées - CNRS (UMR 5572), Laboratoire d¿Astrophysique de Toulouse-Tarbes, 14 Av. Edouard Belin, 31400, France ; Shahram Hosseini

This paper concerns blind mixture identification (BMI) and blind source separation (BSS). We consider non-stationary stochastic sources, more specifically sources with slight time-domain sparsity. We first propose a correlation-based BMI/BSS method for Linear-Quadratic mixtures, called LQ-TEMPCORR. We also investigate the applicability of this type of method to possibly statistically dependent (e.g. correlated) but linearly independent signals. We thus extend the scope of our linear instantaneous method LI-TEMPCORR as a spin-off of this new investigation.

Published in:

Signal Processing and Its Applications, 2007. ISSPA 2007. 9th International Symposium on

Date of Conference:

12-15 Feb. 2007