{"title":"A filter design to increase accuracy of Lucy-Richardson deconvolution for analyzing RTN mixtures effects on VLSI reliability margin","authors":"H. Yamauchi, Worawit Somha, Yuan-Qiang Song","doi":"10.1109/SOCC.2015.7406925","DOIUrl":null,"url":null,"abstract":"A filter design to improve convergence characteristics in the Lucy-Richardson-deconvolution (LRDec) iterations is proposed, which is required for inversely analyzing log-mixtures 7-segmented Random Telegraph Noise (RTN) distribution effects on VLSI reliability margin. The proposed filter alleviates unwanted phase misalignment between the two distribution curves of feedback gain and deconvoluted RTN. This contributes to reduce its relative deconvolution errors by 1.5-orders of magnitude compared with the conventional LRDec. The accuracy of the fail-bit-count (FBC) prediction is increased by 10-folds while accelerating its convergence speed by 7 times of the conventional one. This contributes not to give up on a benefit of smaller iteration cycles from LRDec.","PeriodicalId":329464,"journal":{"name":"2015 28th IEEE International System-on-Chip Conference (SOCC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 28th IEEE International System-on-Chip Conference (SOCC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SOCC.2015.7406925","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
A filter design to improve convergence characteristics in the Lucy-Richardson-deconvolution (LRDec) iterations is proposed, which is required for inversely analyzing log-mixtures 7-segmented Random Telegraph Noise (RTN) distribution effects on VLSI reliability margin. The proposed filter alleviates unwanted phase misalignment between the two distribution curves of feedback gain and deconvoluted RTN. This contributes to reduce its relative deconvolution errors by 1.5-orders of magnitude compared with the conventional LRDec. The accuracy of the fail-bit-count (FBC) prediction is increased by 10-folds while accelerating its convergence speed by 7 times of the conventional one. This contributes not to give up on a benefit of smaller iteration cycles from LRDec.