{"title":"一种优化模拟电路的混合遗传算法","authors":"S. Papadopoulos, R. Mack, R. Massara","doi":"10.1109/MWSCAS.2000.951605","DOIUrl":null,"url":null,"abstract":"An approach is presented for the automated sizing of analog circuits based upon a combination of a genetic algorithm (GA) with a least squares (Gauss-Newton) gradient search. The method combines the global-search properties of the GA with the fast local convergence properties of the least squares method to produce a circuit design from random initial component values in a reduced time compared to the application of a direct GA method, or a restart least squares algorithm. Results are presented to demonstrate the application of the method in the design of both passive and active circuits.","PeriodicalId":437349,"journal":{"name":"Proceedings of the 43rd IEEE Midwest Symposium on Circuits and Systems (Cat.No.CH37144)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2000-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"15","resultStr":"{\"title\":\"A hybrid genetic algorithm method for optimizing analog circuits\",\"authors\":\"S. Papadopoulos, R. Mack, R. Massara\",\"doi\":\"10.1109/MWSCAS.2000.951605\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"An approach is presented for the automated sizing of analog circuits based upon a combination of a genetic algorithm (GA) with a least squares (Gauss-Newton) gradient search. The method combines the global-search properties of the GA with the fast local convergence properties of the least squares method to produce a circuit design from random initial component values in a reduced time compared to the application of a direct GA method, or a restart least squares algorithm. Results are presented to demonstrate the application of the method in the design of both passive and active circuits.\",\"PeriodicalId\":437349,\"journal\":{\"name\":\"Proceedings of the 43rd IEEE Midwest Symposium on Circuits and Systems (Cat.No.CH37144)\",\"volume\":\"21 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2000-08-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"15\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 43rd IEEE Midwest Symposium on Circuits and Systems (Cat.No.CH37144)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/MWSCAS.2000.951605\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 43rd IEEE Midwest Symposium on Circuits and Systems (Cat.No.CH37144)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MWSCAS.2000.951605","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A hybrid genetic algorithm method for optimizing analog circuits
An approach is presented for the automated sizing of analog circuits based upon a combination of a genetic algorithm (GA) with a least squares (Gauss-Newton) gradient search. The method combines the global-search properties of the GA with the fast local convergence properties of the least squares method to produce a circuit design from random initial component values in a reduced time compared to the application of a direct GA method, or a restart least squares algorithm. Results are presented to demonstrate the application of the method in the design of both passive and active circuits.