{"title":"Comparison of gross errors detection methods in process data","authors":"D. Maquin, J. Ragot","doi":"10.1109/CDC.1991.261549","DOIUrl":null,"url":null,"abstract":"The authors first discuss the fundamental problem of data reconciliation. They then prove the equivalence of some tests commonly used for gross error detection: parity vector, normalized corrective terms, the generalized likelihood ratio test, and variation of the residual criterion after measurement deletion.<<ETX>>","PeriodicalId":344553,"journal":{"name":"[1991] Proceedings of the 30th IEEE Conference on Decision and Control","volume":"263 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1991-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"15","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"[1991] Proceedings of the 30th IEEE Conference on Decision and Control","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CDC.1991.261549","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 15
Abstract
The authors first discuss the fundamental problem of data reconciliation. They then prove the equivalence of some tests commonly used for gross error detection: parity vector, normalized corrective terms, the generalized likelihood ratio test, and variation of the residual criterion after measurement deletion.<>
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