{"title":"d稳定IIR滤波器设计的粒子群算法","authors":"Shing‐Tai Pan, Cheng-Yuan Chang","doi":"10.1109/WCICA.2011.5970588","DOIUrl":null,"url":null,"abstract":"This paper explores the design of robust stable digital filter by the Particle Swarm Optimization (PSO) algorithm. The results are compared to the design by Genetic Algorithm (GA). We first derive a robust stability criterion which will be used to ensure the D(α, r) -stability of the digital filter in the evolution of DE. Finally, we will compare the result designed by DE with that designed by GA. It will be found that the performance of the PSO is better that that of GA in the design example of this paper.","PeriodicalId":211049,"journal":{"name":"2011 9th World Congress on Intelligent Control and Automation","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2011-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"14","resultStr":"{\"title\":\"Particle Swarm Optimization on D-stable IIR filter design\",\"authors\":\"Shing‐Tai Pan, Cheng-Yuan Chang\",\"doi\":\"10.1109/WCICA.2011.5970588\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper explores the design of robust stable digital filter by the Particle Swarm Optimization (PSO) algorithm. The results are compared to the design by Genetic Algorithm (GA). We first derive a robust stability criterion which will be used to ensure the D(α, r) -stability of the digital filter in the evolution of DE. Finally, we will compare the result designed by DE with that designed by GA. It will be found that the performance of the PSO is better that that of GA in the design example of this paper.\",\"PeriodicalId\":211049,\"journal\":{\"name\":\"2011 9th World Congress on Intelligent Control and Automation\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-06-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"14\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2011 9th World Congress on Intelligent Control and Automation\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/WCICA.2011.5970588\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 9th World Congress on Intelligent Control and Automation","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WCICA.2011.5970588","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Particle Swarm Optimization on D-stable IIR filter design
This paper explores the design of robust stable digital filter by the Particle Swarm Optimization (PSO) algorithm. The results are compared to the design by Genetic Algorithm (GA). We first derive a robust stability criterion which will be used to ensure the D(α, r) -stability of the digital filter in the evolution of DE. Finally, we will compare the result designed by DE with that designed by GA. It will be found that the performance of the PSO is better that that of GA in the design example of this paper.
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