A linear feedforward neural network with lateral feedback connections for blind source separation

We presents a new necessary and sufficient condition for the blind separation of sources having non-zero kurtosis, from their linear mixtures. It is shown here that a new blind separation criterion based on both odd (f(y)=y³) and even (f(y)=y²) functions, presents desirable solutions, provided that all source signals have negative kurtosis (sub-Gaussian) or have positive kurtosis (super-Gaussian). Based on this new separation criterion, a linear feedforward network with lateral feedback connections is constructed. Both theoretical and computer simulation results are presented