The Complex Blind Deflation Algorithm Based Particle Swarm Optimization with Survival of the Fittest Mechanism
For multi-constraint nonlinear optimization,this paper puts forward a complex blind deflation algorithm based particle swarm optimization with survival of the fittest mechanism(CBD-PSOSFM) which has faster convergence speed,and then gives a quantificational formula of the improved convergence speed,discusses implement method and the rule of parameters design; Because of the blind source separation (BSS) optimization characteristic in nature,the algorithm can be used to implement semi-BSS with nonlinear multi-constraint.For active object echo detection,the paper sets up fitness function with the multi-constraint like as kurtosis,energy and outline and forms the complex blind deflation algorithm.Finally,the simulation experiment of blind deflation to complex echo validates the algorithms validity and faster convergence capability.
particle swarm optimization (PSO) complex signal blind deflation algorithm
Zhao Wei Dong Chunpeng
School of Marine Engineering Northwestern Polytechnical University Xian, China The 705 Research Institute China Shipbuilding Industry Corporation Xian, China
国际会议
太原
英文
411-414
2013-04-06（万方平台首次上网日期，不代表论文的发表时间）