关键词: 听觉信号分离, 粒子群算法, 模拟退火, 自适应变异, 负熵, 盲分离

Abstract: A novel Hybrid Particle Swarm Optimization（HPSO） algorithm combined with the ideal of adaptive population mutation and individual annealing operation is proposed to solve the problem of slow searching speed and low computational precision of basic particle swarm optimization to blind source separation.Compared with Simulated Annealing（SA） and basic Particle Swarm Optimization（PSO），the HPSO is almost as simple for implementation as standard particle swarm optimization，but can carry on mutation adaptively and improve the abilities of seeking the global excellent result and evolution speed.The simulated results show that the effect of separation with the proposed approach is very well，and the blind source separation has not only the character of fast convergence speed but of stable performance.

Key words: acoustic signal separation, particle swarm algorithm, simulated annealing, adaptive mutation, negentropy, blind source separation