高斯混合模型的一种新的统计极大运算及其评价

S. Tsukiyama, M. Fukui
{"title":"高斯混合模型的一种新的统计极大运算及其评价","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":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2011-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"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\":null,\"pages\":null},\"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}","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

摘要

在统计静态时序分析(S-STA)中,将门延迟、信号到达时间、松弛时间等时序信息视为随机变量,统计最大运算是重要的基础运算。由于两个高斯随机变量的最大值不是高斯的,因此提出了各种表示非高斯分布的技术。其中,高斯混合模型与其他模型的不同之处在于,它可以很容易地处理各种相关性、非高斯分布和旋转分布,这在S-STA中很重要。本文提出了一种考虑累积分布函数曲线的高斯混合模型统计极大值运算,并给出了一些实验结果来评价其性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A new statistical maximum operation for Gaussian mixture models and its evaluations
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.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信