{"title":"人工神经网络在模拟版图布局设计中的应用","authors":"Rui He, Lihong Zhang","doi":"10.1109/CCECE.2009.5090269","DOIUrl":null,"url":null,"abstract":"In this paper, we propose a method using mean-field neural networks to solve the placement problem for the layout design of analog integrated circuits. By means of the energy function, our method can not only meet the basic requirements of placement, but also handle the symmetry and proximity constraints that are special for analog layouts. Compared with other work, our experimental results show this proposed optimization scheme can achieve more efficient performance and obtain optimal solutions.","PeriodicalId":153464,"journal":{"name":"2009 Canadian Conference on Electrical and Computer Engineering","volume":"19 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Artificial neural network application in analog layout placement design\",\"authors\":\"Rui He, Lihong Zhang\",\"doi\":\"10.1109/CCECE.2009.5090269\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we propose a method using mean-field neural networks to solve the placement problem for the layout design of analog integrated circuits. By means of the energy function, our method can not only meet the basic requirements of placement, but also handle the symmetry and proximity constraints that are special for analog layouts. Compared with other work, our experimental results show this proposed optimization scheme can achieve more efficient performance and obtain optimal solutions.\",\"PeriodicalId\":153464,\"journal\":{\"name\":\"2009 Canadian Conference on Electrical and Computer Engineering\",\"volume\":\"19 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-05-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 Canadian Conference on Electrical and Computer Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CCECE.2009.5090269\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 Canadian Conference on Electrical and Computer Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CCECE.2009.5090269","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Artificial neural network application in analog layout placement design
In this paper, we propose a method using mean-field neural networks to solve the placement problem for the layout design of analog integrated circuits. By means of the energy function, our method can not only meet the basic requirements of placement, but also handle the symmetry and proximity constraints that are special for analog layouts. Compared with other work, our experimental results show this proposed optimization scheme can achieve more efficient performance and obtain optimal solutions.