Contrast Functions for Blind Separation and Deconvolution of Sources
نویسنده
چکیده
A general method to construct contrast functions for blind source separation is presented. It is based on a superadditive functional of class II applied to the distributions of the reconstructed sources. Examples of such functionals are given. Our approach permits exploiting the temporal dependence of the sources by using a functional on the joint distribution of the source process over a time interval. This yields many new examples and frees us from the constraint that the sources be non Gaussian. Contrasts functions based on cumulants requiring the orthogonality constraint is also covered. Finally, the case of convolutive mixtures is considered in relation with the problem of blind separationdeconvolution.
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