关键词: 盲分离, 果蝇优化, 规范四阶累积量

Abstract: The basic theory of Fruit Fly Optimization Algorithm（FOA） is introduced. According to the stability and Convergence of FastICA is not enough, and the Blind Source Separation（BSS） of particle swarm optimization is not fast enough, the improved fruit fly optimization algorithm is being applied in researching of BSS, and a new BSS algorithm is proposed. The absolute value of normalized fourth-order cumulant is used in the algorithm as cost function and the improved Fruit Fly Optimization Algorithm is used to optimize the cost function. One by one to determine the separation vector and the instantaneous linear mixed blind source audio signal could be separated in sequence. In the meantime, the simulation results show that the algorithm can achieve the efficient sequential blind separation for source signal and ensure the separation order according to the descending absolute value of normalized fourth-order cumulant, and has higher separation accuracy.

Key words: blind source separation, Fruit Fly Optimization Algorithm, normalized fourth-order cumulant