CRITERIA FOR MULTICHANNEL SIGNAL SEPARATION

We consider the problem in which we want to separate two (or more) sig nals that are coupled to each other through an unknown multiple-input- multiple-output linear system (channel). We prove that the signals can be decoupled, or separated, using only the condition that they are st atistically independent, and find even weaker sufficient conditions in volving their cross-polyspectra. By imposing these. conditions on the reconstructed signals, we obtain a class of criteria for signal separa tion. These criteria are universal in the sense that they do not requi re any prior knowledge or information concerning the nature of the sou rce signals. They may be communication signals, or speech signals, or any other 1-D or multidimensional signals (e.g., images). Computationa lly efficient algorithms for implementing the proposed criteria, that only involve the iterative solution to a linear least squares problem, are presented.