{"title":"A mixed-domain behavioral model's extraction for digital I/O buffers","authors":"W. Dghais, T. Cunha, J. Pedro","doi":"10.1109/EPEPS.2012.6457882","DOIUrl":null,"url":null,"abstract":"The paper presents a novel extraction procedure based on the frequency domain formulation of the current-charge (I-Q) behavioral model for digital I/O buffers/drivers output admittance followed by a time domain extraction of the predriver's nonlinear dynamic functions. The large signal model's functions of the drivers' output admittance are derived from the bias-dependent scattering, or S-parameters, measurements. This easy and fast extraction method allows the accurate generation of the data-based model from automated and straightforward measurements. The extracted model's functions are implemented as lookup tables (LUTs) and the behavioral model is validated in typical SI scenario.","PeriodicalId":188377,"journal":{"name":"2012 IEEE 21st Conference on Electrical Performance of Electronic Packaging and Systems","volume":"106 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 IEEE 21st Conference on Electrical Performance of Electronic Packaging and Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/EPEPS.2012.6457882","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 8
Abstract
The paper presents a novel extraction procedure based on the frequency domain formulation of the current-charge (I-Q) behavioral model for digital I/O buffers/drivers output admittance followed by a time domain extraction of the predriver's nonlinear dynamic functions. The large signal model's functions of the drivers' output admittance are derived from the bias-dependent scattering, or S-parameters, measurements. This easy and fast extraction method allows the accurate generation of the data-based model from automated and straightforward measurements. The extracted model's functions are implemented as lookup tables (LUTs) and the behavioral model is validated in typical SI scenario.
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