文章基本信息

标题：Non-asymptotic Confidence Regions for Errors-In-Variables Systems in an Extended Noise Environment
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作者：Masoud Moravej Khorasani ; Erik Weyer
期刊名称：IFAC PapersOnLine
印刷版ISSN：2405-8963
出版年度：2021
卷号：54
期号：7
页码：583-588
DOI：10.1016/j.ifacol.2021.08.423
语种：English
出版社：Elsevier
摘要：AbstractIn this paper we consider the problem of constructing non-asymptotic confidence regions for the parameters of Errors-In-Variables systems where both inputs and outputs are contaminated by noise terms. The proposed method is based upon extending the Sign-Perturbed Sums (SPS) method for EIV systems in (Moravej Khorasani and Weyer (2020a)) to the case where the noise terms and input are modeled as ARMA systems driven by i.i.d. Gaussian processes. It is shown that the constructed confidence region include the true parameter with a user chosen probability for any finite number of data points. The method is illustrated in a simulation example.
关键词：Keywordssystem identificationconfidence regionserrors-in-variablefinite sample system identification