Blind separation based on an evolutionary neural network

We propose an evolutionary neural network for blind source separation. In the proposed method, the separating matrix is used as connection weights of the network, which are updated by a genetic algorithm. A higher-order statistics of kurtosis, which is a simple and original criterion for independence, is used as a fitness function. The applicability of the proposed method for blind source separation is demonstrated by the simulation results