{"title":"基于综合学习粒子群优化(CLPSO)算法的交叉耦合谐振滤波器合成","authors":"A. Azad, D. Jhariya, A. Mohan","doi":"10.1109/APMC.2016.7931388","DOIUrl":null,"url":null,"abstract":"This paper presents the synthesis of coupling matrix of cross-coupled resonator filters using comprehensive learning particle swarm optimization (CLPSO) algorithm. The CLPSO algorithm does not require gradient information of the fitness function under consideration. The coupling topology of the filter is incorporated in the optimization process to eliminate the need of similarity transformations of the coupling matrix. The CLPSO algorithm is applied to synthesize third- and fourth-order cross-coupled resonator filters.","PeriodicalId":166478,"journal":{"name":"2016 Asia-Pacific Microwave Conference (APMC)","volume":"52 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Synthesis of cross-coupled resonator filters using comprehensive learning particle swarm optimization (CLPSO) algorithm\",\"authors\":\"A. Azad, D. Jhariya, A. Mohan\",\"doi\":\"10.1109/APMC.2016.7931388\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents the synthesis of coupling matrix of cross-coupled resonator filters using comprehensive learning particle swarm optimization (CLPSO) algorithm. The CLPSO algorithm does not require gradient information of the fitness function under consideration. The coupling topology of the filter is incorporated in the optimization process to eliminate the need of similarity transformations of the coupling matrix. The CLPSO algorithm is applied to synthesize third- and fourth-order cross-coupled resonator filters.\",\"PeriodicalId\":166478,\"journal\":{\"name\":\"2016 Asia-Pacific Microwave Conference (APMC)\",\"volume\":\"52 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 Asia-Pacific Microwave Conference (APMC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/APMC.2016.7931388\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 Asia-Pacific Microwave Conference (APMC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/APMC.2016.7931388","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Synthesis of cross-coupled resonator filters using comprehensive learning particle swarm optimization (CLPSO) algorithm
This paper presents the synthesis of coupling matrix of cross-coupled resonator filters using comprehensive learning particle swarm optimization (CLPSO) algorithm. The CLPSO algorithm does not require gradient information of the fitness function under consideration. The coupling topology of the filter is incorporated in the optimization process to eliminate the need of similarity transformations of the coupling matrix. The CLPSO algorithm is applied to synthesize third- and fourth-order cross-coupled resonator filters.