{"title":"一种将模型参数变化与过程波动联系起来的方法","authors":"J. A. Power, A. Mathewson, W. Lane","doi":"10.1109/ICMTS.1993.292892","DOIUrl":null,"url":null,"abstract":"A methodology that makes it possible to link circuit simulator model parameter variations and correlations to disturbances in the IC manufacturing process is presented. An example in which the variabilities among a set of 30 correlated empirical MOSFET model parameters from a 2- mu m CMOS process are represented by the variabilities of just six uncorrelated components with the aid of principal component analysis (PCA) and VARIMAX transformations is described. The derived uncorrelated components are interpreted in terms of the probable process input fluctuations causing them. These independent components may then be utilized to form the basis of realistic worst-case design methodologies or more rigorous statistical design techniques.<<ETX>>","PeriodicalId":123048,"journal":{"name":"ICMTS 93 Proceedings of the 1993 International Conference on Microelectronic Test Structures","volume":"34 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1993-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"21","resultStr":"{\"title\":\"An approach for relating model parameter variabilities to process fluctuations\",\"authors\":\"J. A. Power, A. Mathewson, W. Lane\",\"doi\":\"10.1109/ICMTS.1993.292892\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A methodology that makes it possible to link circuit simulator model parameter variations and correlations to disturbances in the IC manufacturing process is presented. An example in which the variabilities among a set of 30 correlated empirical MOSFET model parameters from a 2- mu m CMOS process are represented by the variabilities of just six uncorrelated components with the aid of principal component analysis (PCA) and VARIMAX transformations is described. The derived uncorrelated components are interpreted in terms of the probable process input fluctuations causing them. These independent components may then be utilized to form the basis of realistic worst-case design methodologies or more rigorous statistical design techniques.<<ETX>>\",\"PeriodicalId\":123048,\"journal\":{\"name\":\"ICMTS 93 Proceedings of the 1993 International Conference on Microelectronic Test Structures\",\"volume\":\"34 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1993-03-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"21\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ICMTS 93 Proceedings of the 1993 International Conference on Microelectronic Test Structures\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICMTS.1993.292892\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ICMTS 93 Proceedings of the 1993 International Conference on Microelectronic Test Structures","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICMTS.1993.292892","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 21
摘要
提出了一种方法,使电路模拟器模型参数变化和相关性与集成电路制造过程中的干扰联系起来成为可能。本文描述了一个2 μ m CMOS工艺中30个相关经验MOSFET模型参数的变异性,通过主成分分析(PCA)和VARIMAX变换,用6个不相关分量的变异性来表示。导出的不相关分量根据引起它们的可能过程输入波动来解释。然后,这些独立的成分可以用来形成现实的最坏情况设计方法或更严格的统计设计技术的基础。
An approach for relating model parameter variabilities to process fluctuations
A methodology that makes it possible to link circuit simulator model parameter variations and correlations to disturbances in the IC manufacturing process is presented. An example in which the variabilities among a set of 30 correlated empirical MOSFET model parameters from a 2- mu m CMOS process are represented by the variabilities of just six uncorrelated components with the aid of principal component analysis (PCA) and VARIMAX transformations is described. The derived uncorrelated components are interpreted in terms of the probable process input fluctuations causing them. These independent components may then be utilized to form the basis of realistic worst-case design methodologies or more rigorous statistical design techniques.<>