{"title":"A new statistical maximum operation for Gaussian mixture models and its evaluations","authors":"S. Tsukiyama, M. Fukui","doi":"10.1109/ECCTD.2011.6043378","DOIUrl":null,"url":null,"abstract":"In the statistical static timing analysis (S-STA), the timing information, such as a gate delay, a signal arrival time, and a slack, is treated as a random variable, and the statistical maximum operation is an important basic operation. Since the maximum of two Gaussian random variables is not Gaussian, various techniques for representing a non-Gaussian distribution have been proposed. Among them, the Gaussian mixture model is distinguished from the others in that it can handle various correlations, non-Gaussian distributions, and slew distributions easily, which are important in S-STA. In this paper, we propose a new statistical maximum operation for Gaussian mixture models, which takes the cumulative distribution function curve into account, and show some experimental results to evaluate its performance.","PeriodicalId":126960,"journal":{"name":"2011 20th European Conference on Circuit Theory and Design (ECCTD)","volume":"143 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 20th European Conference on Circuit Theory and Design (ECCTD)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ECCTD.2011.6043378","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
In the statistical static timing analysis (S-STA), the timing information, such as a gate delay, a signal arrival time, and a slack, is treated as a random variable, and the statistical maximum operation is an important basic operation. Since the maximum of two Gaussian random variables is not Gaussian, various techniques for representing a non-Gaussian distribution have been proposed. Among them, the Gaussian mixture model is distinguished from the others in that it can handle various correlations, non-Gaussian distributions, and slew distributions easily, which are important in S-STA. In this paper, we propose a new statistical maximum operation for Gaussian mixture models, which takes the cumulative distribution function curve into account, and show some experimental results to evaluate its performance.