{"title":"模拟电路设计采用带有模糊适应度函数的遗传算法","authors":"Hector Hostos, Federico Sanabria, M. Melgarejo","doi":"10.1109/ANDESCON.2010.5633391","DOIUrl":null,"url":null,"abstract":"This paper presents an approach to the design of analog circuits based on operational amplifiers using genetic algorithms. The input parameter is the transfer function of the required system. The fitness function of the genetic algorithm is implemented by means of a fuzzy inference system. This article includes the synthesis of the methodology used in the design and also some results with a specific topology for two transfer functions.","PeriodicalId":359559,"journal":{"name":"2010 IEEE ANDESCON","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Analog circuit design using genetic algorithms with fuzzy fitness function\",\"authors\":\"Hector Hostos, Federico Sanabria, M. Melgarejo\",\"doi\":\"10.1109/ANDESCON.2010.5633391\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents an approach to the design of analog circuits based on operational amplifiers using genetic algorithms. The input parameter is the transfer function of the required system. The fitness function of the genetic algorithm is implemented by means of a fuzzy inference system. This article includes the synthesis of the methodology used in the design and also some results with a specific topology for two transfer functions.\",\"PeriodicalId\":359559,\"journal\":{\"name\":\"2010 IEEE ANDESCON\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-11-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 IEEE ANDESCON\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ANDESCON.2010.5633391\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 IEEE ANDESCON","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ANDESCON.2010.5633391","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Analog circuit design using genetic algorithms with fuzzy fitness function
This paper presents an approach to the design of analog circuits based on operational amplifiers using genetic algorithms. The input parameter is the transfer function of the required system. The fitness function of the genetic algorithm is implemented by means of a fuzzy inference system. This article includes the synthesis of the methodology used in the design and also some results with a specific topology for two transfer functions.
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