{"title":"基于自适应遗传算法的CMOS模拟电路参数优化自动化设计方法","authors":"Jianhai Yu, Zhigang Mao","doi":"10.1109/ICASIC.2007.4415854","DOIUrl":null,"url":null,"abstract":"A new method for optimizing the parameters of CMOS analog circuits based on adaptive EGA (elitist genetic algorithm) is proposed in this paper. In the method the Hspice simulation tool is called to evaluate the fitness of every circuit repeatedly in a generation. According to the results of the evaluation better circuits can be reserved. By adjusting the parameters of transistors through EGA the evolution can find the circuit which will satisfy our specifications. The outcome of the experiment for a two-stage operational amplifier shows that this is an accurate and promising way in determining the device sizes in an analog circuit.","PeriodicalId":120984,"journal":{"name":"2007 7th International Conference on ASIC","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2007-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"20","resultStr":"{\"title\":\"Automated design method for parameters optimization of CMOS analog circuits based on adaptive genetic algorithm\",\"authors\":\"Jianhai Yu, Zhigang Mao\",\"doi\":\"10.1109/ICASIC.2007.4415854\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A new method for optimizing the parameters of CMOS analog circuits based on adaptive EGA (elitist genetic algorithm) is proposed in this paper. In the method the Hspice simulation tool is called to evaluate the fitness of every circuit repeatedly in a generation. According to the results of the evaluation better circuits can be reserved. By adjusting the parameters of transistors through EGA the evolution can find the circuit which will satisfy our specifications. The outcome of the experiment for a two-stage operational amplifier shows that this is an accurate and promising way in determining the device sizes in an analog circuit.\",\"PeriodicalId\":120984,\"journal\":{\"name\":\"2007 7th International Conference on ASIC\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2007-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"20\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2007 7th International Conference on ASIC\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICASIC.2007.4415854\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2007 7th International Conference on ASIC","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICASIC.2007.4415854","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Automated design method for parameters optimization of CMOS analog circuits based on adaptive genetic algorithm
A new method for optimizing the parameters of CMOS analog circuits based on adaptive EGA (elitist genetic algorithm) is proposed in this paper. In the method the Hspice simulation tool is called to evaluate the fitness of every circuit repeatedly in a generation. According to the results of the evaluation better circuits can be reserved. By adjusting the parameters of transistors through EGA the evolution can find the circuit which will satisfy our specifications. The outcome of the experiment for a two-stage operational amplifier shows that this is an accurate and promising way in determining the device sizes in an analog circuit.