Bilnd Source Separation in Nonlinear Mixtures, Ph.D. Dissertation Sharif University of Technology ; Babaiezadeh, Massoud (Supervisor) ; Jutten, Christian (Co-Supervisor) ; Rivet, Bertrand (Co-Supervisor)
Abstract
Blind Source Separation (BSS) is a technique for estimating individual source components from their mixtures at multiple sensors, where the mixing model is unknown. Although it has been mathematically shown that for linear mixtures, under mild conditions, mutually independent sources can be reconstructed up to accepted ambiguities, there is not such theoretical basis for general nonlinear models. This is why there are relatively few resultsin the literature in this regard in the recent decades, which are focused on specific structured nonlinearities.In the present study, the problem is tackled using a novel approach utilizing temporal information of the signals. The original idea followed in...
Cataloging briefBilnd Source Separation in Nonlinear Mixtures, Ph.D. Dissertation Sharif University of Technology ; Babaiezadeh, Massoud (Supervisor) ; Jutten, Christian (Co-Supervisor) ; Rivet, Bertrand (Co-Supervisor)
Abstract
Blind Source Separation (BSS) is a technique for estimating individual source components from their mixtures at multiple sensors, where the mixing model is unknown. Although it has been mathematically shown that for linear mixtures, under mild conditions, mutually independent sources can be reconstructed up to accepted ambiguities, there is not such theoretical basis for general nonlinear models. This is why there are relatively few resultsin the literature in this regard in the recent decades, which are focused on specific structured nonlinearities.In the present study, the problem is tackled using a novel approach utilizing temporal information of the signals. The original idea followed in...
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