Title :
Blind identification and separation methods for Linear-Quadratic mixtures and/or linearly independent non-stationary signals
Author :
Deville, Yannick ; Hosseini, Shahram
Author_Institution :
Obs. Midi-Pyrenees, Univ. Paul Sabatier Toulouse 3, Toulouse
Abstract :
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.
Keywords :
blind source separation; stochastic processes; LI-TEMPCORR; LQ-TEMPCORR; blind identification; blind mixture identification; blind separation; blind source separation; linear instantaneous method; linear-quadratic mixtures; linearly independent nonstationary signals; nonstationary stochastic sources; Blind source separation; Independent component analysis; Signal processing; Source separation; Stochastic processes; Time domain analysis; Vectors;
Conference_Titel :
Signal Processing and Its Applications, 2007. ISSPA 2007. 9th International Symposium on
Conference_Location :
Sharjah
Print_ISBN :
978-1-4244-0778-1
Electronic_ISBN :
978-1-4244-1779-8
DOI :
10.1109/ISSPA.2007.4555477