{"title":"自适应全局最佳导向杜鹃搜索算法在FIR滤波器设计中的应用","authors":"P. Das, S. Naskar, S. N. Patra","doi":"10.1109/ICRCICN.2017.8234474","DOIUrl":null,"url":null,"abstract":"In this paper, we propose design of even order low pass FIR filter and odd order bandpass FIR filter using coefficients optimized by an adaptive Global Best steered Cuckoo Search Algorithm (gbest CSA). For optimization, we use a mean square error based cost function as the fitness function. We evaluated the efficacy of the proposed technique by comparing the filter responses with responses of the filters designed using standard Cuckoo Search Algorithm and traditional technique of filter design with Parks McClellan algorithm. Efficacy of the proposed algorithm compared to the conventional CSA is proved using seven standard benchmark functions.","PeriodicalId":166298,"journal":{"name":"2017 Third International Conference on Research in Computational Intelligence and Communication Networks (ICRCICN)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Adaptive global best steered Cuckoo search algorithm for FIR filter design\",\"authors\":\"P. Das, S. Naskar, S. N. Patra\",\"doi\":\"10.1109/ICRCICN.2017.8234474\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we propose design of even order low pass FIR filter and odd order bandpass FIR filter using coefficients optimized by an adaptive Global Best steered Cuckoo Search Algorithm (gbest CSA). For optimization, we use a mean square error based cost function as the fitness function. We evaluated the efficacy of the proposed technique by comparing the filter responses with responses of the filters designed using standard Cuckoo Search Algorithm and traditional technique of filter design with Parks McClellan algorithm. Efficacy of the proposed algorithm compared to the conventional CSA is proved using seven standard benchmark functions.\",\"PeriodicalId\":166298,\"journal\":{\"name\":\"2017 Third International Conference on Research in Computational Intelligence and Communication Networks (ICRCICN)\",\"volume\":\"5 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 Third International Conference on Research in Computational Intelligence and Communication Networks (ICRCICN)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICRCICN.2017.8234474\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 Third International Conference on Research in Computational Intelligence and Communication Networks (ICRCICN)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICRCICN.2017.8234474","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Adaptive global best steered Cuckoo search algorithm for FIR filter design
In this paper, we propose design of even order low pass FIR filter and odd order bandpass FIR filter using coefficients optimized by an adaptive Global Best steered Cuckoo Search Algorithm (gbest CSA). For optimization, we use a mean square error based cost function as the fitness function. We evaluated the efficacy of the proposed technique by comparing the filter responses with responses of the filters designed using standard Cuckoo Search Algorithm and traditional technique of filter design with Parks McClellan algorithm. Efficacy of the proposed algorithm compared to the conventional CSA is proved using seven standard benchmark functions.