Blind separation and restoration of signals mixed in convolutive environment

This paper proposes new neural network approaches for separating and restoring signals mixed through FIR channels. Firstly, a set of maximal entropy based training rules are developed. Secondly, a new scheme for restoring the original signals is proposed for the 2/spl times/2 case. Computer simulation results for speech signals are presented to verify the proposed approaches.