{"title":"Dynamic power consumption of distributed RLC trees","authors":"Xiaochun Li, J. Mao, W. Yin","doi":"10.1109/ICASIC.2007.4415857","DOIUrl":null,"url":null,"abstract":"Based on Fourier series analysis, an analytical model of dynamic power of distributed RLC trees is presented. In the model, the dynamic power consumption is approximated by the summation of the first several odd-order components. Each component is calculated by an iterative algorithm of the input admittance function of the tree with no approximation. The error of the model with five components is less than 5% and arbitrarily desired accurate results can be obtained by including appropriate number of components. The model is significantly much faster than SPICE and its computation complexity is linear with the number of components and branches in the tree.","PeriodicalId":120984,"journal":{"name":"2007 7th International Conference on ASIC","volume":"26 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2007-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2007 7th International Conference on ASIC","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICASIC.2007.4415857","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
Based on Fourier series analysis, an analytical model of dynamic power of distributed RLC trees is presented. In the model, the dynamic power consumption is approximated by the summation of the first several odd-order components. Each component is calculated by an iterative algorithm of the input admittance function of the tree with no approximation. The error of the model with five components is less than 5% and arbitrarily desired accurate results can be obtained by including appropriate number of components. The model is significantly much faster than SPICE and its computation complexity is linear with the number of components and branches in the tree.
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