Blind Sparse Source Separation Based on Particle Swarm Optimization
Zhaohui Li · Jisuanji fangzhen · 2006
A blind sparse source separation algorithm was proposed by using the particle swarm optimization.The proposed algorithm first estimates the mixing matrix by using the particle-swarm-optimization-based clustering algorithm.Then the particle swarm optimization which always meets the constraints except for initialsing all particles to be feasible solutions in solving linearly constrained optimization problem is applied to the linearly constrained optimization problem for recovering the sparse sources.The presented algorithm is characterized by high accuracy and less computation.Simulation results illustrate the efficiency and the good performance of the algorithm.