文章基本信息

标题：EM-based identification of static errors-in-variables systems utilizing Gaussian Mixture models ⁎
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作者：Angel L. Cedeño ; Rafael Orellana ; Rodrigo Carvajal 等
期刊名称：IFAC PapersOnLine
印刷版ISSN：2405-8963
出版年度：2020
卷号：53
期号：2
页码：863-868
DOI：10.1016/j.ifacol.2020.12.844
语种：English
出版社：Elsevier
摘要：AbstractIn this paper we address the problem of identifying a static errors-in-variables system. Our proposal is based on the Expectation-Maximization algorithm, in which we consider that the distribution of the noise-free input is approximated by a finite Gaussian mixture. This approach allows us to estimate the static system parameters, the input and output noise variances, and the Gaussian mixture parameters. We show the benefits of our proposal via numerical simulations.
关键词：KeywordsErrors-in-variablesMaximum LikelihoodExpectation-MaximizationGaussian MixtureEstimationOptimization