文章基本信息

标题：Anomaly Detection of Markov Processes with Evolution Equation and Moments ⁎
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作者：Rafal Wisniewski ; Manuela L. Bujorianu
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：1974-1979
DOI：10.1016/j.ifacol.2020.12.2561
语种：English
出版社：Elsevier
摘要：AbstractOur departure point is the evolution equation of a Markov process. It describes the changes in the transition probability as time passes. We compare the transition probability for a priori model with the actual transition probability of the observed process to detect a mismatch between the expected and the measured data. To translate this idea into an algorithm, we characterise the involved measures by their moments. Specifically, a linear dynamic system is put forward that describes the evolution of moments. As the last result, we define a moment divergence as the means of computing the distance between two sequences of moments. We see the work as a step towards merging model-driven and data-driven concepts in control engineering. To elucidate the concepts introduced, we have incorporated several simple examples.