Blind MIMO deconvolution of any source distributions via high-order spectra

This paper is concerned with blind separation of convolutive mixtures of spatially independent, and temporally possible non linear processes. We consider the MIMO extraction based on the maximization of a contrast function. A new self-styled referenced contrast (RC) function is proposed, which is based on cross-trispectra between the estimated output and a reference signal. Using Parsevals formula, the former criterion yields a new class of time-domain contrast. It presents two main advantages over other more traditional contrasts. Firstly, it concerns the computational cost, and secondly the extension takes into consideration the extraction of the independent sources in the presence of Gaussian sources by making some constraints on the reference signals. There is no comparison with other methods because this is the first technique that deals with this kind of signals in the convolutif mixtures.