Adaptive subspace algorithm for blind separation of independent sources in convolutive mixture

The advantage of the algorithm proposed in this correspondence is that it reduces a convolutive mixture to an instantaneous mixture by using only second-order statistics (but more sensors than sources). Furthermore, the sources can be separated by using any algorithm applicable to an instantaneous mixture. Otherwise, to ensure the convergence of our algorithm, we assume some classical assumptions for blind separation of sources and some added subspace assumptions. Finally, the assumptions concerning the subspace model and their properties are emphasized in this correspondence.