{"title":"改进粒子群算法在天线阵方向图合成中的应用","authors":"W. Li, S. Liu, X. Shi","doi":"10.1109/GSMM.2008.4534574","DOIUrl":null,"url":null,"abstract":"Particle swarm optimization (PSO) is a robust stochastic evolutionary computation technique based on the movement and intelligence of swarm, which is very easy to understand and implement. In order to overcome the drawbacks of standard PSO, some improved mechanisms based on the design of a novel formula for velocity updating, and global best perturbation are adopted. The simulation results of sidelobe reduction of 2-D array show that it is effective.","PeriodicalId":304483,"journal":{"name":"2008 Global Symposium on Millimeter Waves","volume":"30 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Application of Improved Particle Swarm Optimization in Antenna Array Pattern Syntheis\",\"authors\":\"W. Li, S. Liu, X. Shi\",\"doi\":\"10.1109/GSMM.2008.4534574\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Particle swarm optimization (PSO) is a robust stochastic evolutionary computation technique based on the movement and intelligence of swarm, which is very easy to understand and implement. In order to overcome the drawbacks of standard PSO, some improved mechanisms based on the design of a novel formula for velocity updating, and global best perturbation are adopted. The simulation results of sidelobe reduction of 2-D array show that it is effective.\",\"PeriodicalId\":304483,\"journal\":{\"name\":\"2008 Global Symposium on Millimeter Waves\",\"volume\":\"30 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2008-04-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2008 Global Symposium on Millimeter Waves\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/GSMM.2008.4534574\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2008 Global Symposium on Millimeter Waves","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/GSMM.2008.4534574","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Application of Improved Particle Swarm Optimization in Antenna Array Pattern Syntheis
Particle swarm optimization (PSO) is a robust stochastic evolutionary computation technique based on the movement and intelligence of swarm, which is very easy to understand and implement. In order to overcome the drawbacks of standard PSO, some improved mechanisms based on the design of a novel formula for velocity updating, and global best perturbation are adopted. The simulation results of sidelobe reduction of 2-D array show that it is effective.