An Adaptive Genetic Algorithm for Blind Source Separation
Huang Shuang-feng · Jisuanji fangzhen · 2009
BSS(Blind Source Separation)and ICA(Independent Component Analysis),which do not require priorknowledge of signals,are widely applied.Independent component analysis(ICA) is a new technique in signal processing.The goal of ICA is to find a separation matrix so that each component of the output signal obtained by transforming the observed multidimensional mixture of data is independent.An adaptive genetic algorithm which combines GA with ICA for blind source separation is proposed in this paper.The convergence and stability of the algorithm are confirmed by comparing with traditional GA.Three sound signals are tested and their validity is confirmed by signal separation test.