{"title":"不变性原理及其在分布式参数识别中的应用","authors":"G. Yin, B. Fitzpatrick","doi":"10.1109/CDC.1990.203486","DOIUrl":null,"url":null,"abstract":"A nonlinear least squares parameter estimation procedure is discussed. The main objective is to extend previous results in order to obtain certain functional invariance theorems. In particular, weak convergence methods are used to prove an asymptotic normality result and Strassen's invariance principle is applied to establish a law of the iterated logarithm. Some examples are presented.<<ETX>>","PeriodicalId":287089,"journal":{"name":"29th IEEE Conference on Decision and Control","volume":"14 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1990-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Invariance principles and applications to distributed parameter identification\",\"authors\":\"G. Yin, B. Fitzpatrick\",\"doi\":\"10.1109/CDC.1990.203486\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A nonlinear least squares parameter estimation procedure is discussed. The main objective is to extend previous results in order to obtain certain functional invariance theorems. In particular, weak convergence methods are used to prove an asymptotic normality result and Strassen's invariance principle is applied to establish a law of the iterated logarithm. Some examples are presented.<<ETX>>\",\"PeriodicalId\":287089,\"journal\":{\"name\":\"29th IEEE Conference on Decision and Control\",\"volume\":\"14 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1990-12-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"29th IEEE Conference on Decision and Control\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CDC.1990.203486\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"29th IEEE Conference on Decision and Control","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CDC.1990.203486","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Invariance principles and applications to distributed parameter identification
A nonlinear least squares parameter estimation procedure is discussed. The main objective is to extend previous results in order to obtain certain functional invariance theorems. In particular, weak convergence methods are used to prove an asymptotic normality result and Strassen's invariance principle is applied to establish a law of the iterated logarithm. Some examples are presented.<>
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