{"title":"Fault Detection And Classification In Linear Microcircuits","authors":"B. R. Epstein, M. Czigler","doi":"10.1109/ELECTR.1991.718227","DOIUrl":null,"url":null,"abstract":"Classical discrimination analysis and neural network techniques are used to detect and classify possible faults in linear microcircuits. The success rates of simulated fault detection and classification are described for various types of analog and mixed-mode circuits.","PeriodicalId":339281,"journal":{"name":"Electro International, 1991","volume":"3 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1991-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Electro International, 1991","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ELECTR.1991.718227","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
Classical discrimination analysis and neural network techniques are used to detect and classify possible faults in linear microcircuits. The success rates of simulated fault detection and classification are described for various types of analog and mixed-mode circuits.