Blind signal separation by an evolutionary neural network with higher-order statistics

In this paper, we propose an evolutionary neural network for blind source separation (BSS). In the proposed method, the separating matrix is used as connection weights of the network, which are updated by a genetic algorithm (GA). 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 simulations.