{"title":"A Multi-population Particle Swarm Optimizer and its Application to Blind Multichannel Estimation","authors":"Ying Gao, Zhaohui Li, Xiao Hu, Huailiang Liu","doi":"10.1109/ICNC.2007.72","DOIUrl":null,"url":null,"abstract":"In this paper, a multi-population particle swarm optimizer based on Lotka-Volterra competition equation is first proposed. The cooperative coevolution in the field of is involved into original particle swarm optimizer, and populations size is adjusted adaptively based on multi- population Lotka-Volterra competition equation. Then, the algorithm is applied to blind multichannel estimation by optimizing an error function for the outputs of a multichannel system. The experiment results demonstrate that the proposed algorithm is superior to original particle swarm optimization algorithm, and is effective to blind multichannel estimation.","PeriodicalId":250881,"journal":{"name":"Third International Conference on Natural Computation (ICNC 2007)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2007-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Third International Conference on Natural Computation (ICNC 2007)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICNC.2007.72","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 6
Abstract
In this paper, a multi-population particle swarm optimizer based on Lotka-Volterra competition equation is first proposed. The cooperative coevolution in the field of is involved into original particle swarm optimizer, and populations size is adjusted adaptively based on multi- population Lotka-Volterra competition equation. Then, the algorithm is applied to blind multichannel estimation by optimizing an error function for the outputs of a multichannel system. The experiment results demonstrate that the proposed algorithm is superior to original particle swarm optimization algorithm, and is effective to blind multichannel estimation.