Blind Separation of Non-Stationary Convolutively Mixed Signals in the Time Domain

This paper proposes a new algorithm for solving the Blind Signal Separation (BSS) problem for convolutive mixing completely in the time domain. The closed form expressions used for first and second order optimization techniques derived in [1] are extended to accommodate the more practical convolutive mixing scenario. Traditionally convolutive BSS problems are solved in the frequency domain [2], [3], [4] but this requires additional solving of the inherent frequency permutation problem. We demonstrate the performance of the algorithm using two optimization methods with a convolutive synthetic mixing system and real speech data.