A new composite criterion for adaptive and iterative blind source separation

When n independent random signals are mixed by an unknown m×n matrix, the task of recovering the original signals from their mixtures is called blind source separation. The article introduces two simple source separation algorithms. The first one is adaptive, the second is iterative. Both work indifferently with complex or real signals and use an estimation equation involving 2nd-order and higher-order information. A key feature is that resulting performance is independent of the mixing matrix in the noiseless case. Simulations also indicate the absence of ill convergence