{"title":"A PLA-based algorithm for estimating transition densities in two-level combinational logic circuits","authors":"T. Her, W. Tsai, F. Kurdahi, Y. Chen","doi":"10.1109/APCCAS.1994.514592","DOIUrl":null,"url":null,"abstract":"We present a model based on the PLA implementation of logic circuits to estimate the transition densities in two-level combinational logic circuits. Given the primary input signal probabilities and transition densities, our model computes the transition densities at the internal and output nodes directly from the sum-of-products representation of the two-level logic circuits without further converting the circuits into other representations. The experimental results from our model compared to those from SPICE simulations are within an average of 1.7% error, confirming the effectiveness of our model.","PeriodicalId":231368,"journal":{"name":"Proceedings of APCCAS'94 - 1994 Asia Pacific Conference on Circuits and Systems","volume":"41 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1994-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of APCCAS'94 - 1994 Asia Pacific Conference on Circuits and Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/APCCAS.1994.514592","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
We present a model based on the PLA implementation of logic circuits to estimate the transition densities in two-level combinational logic circuits. Given the primary input signal probabilities and transition densities, our model computes the transition densities at the internal and output nodes directly from the sum-of-products representation of the two-level logic circuits without further converting the circuits into other representations. The experimental results from our model compared to those from SPICE simulations are within an average of 1.7% error, confirming the effectiveness of our model.