Journal article

Change detection for undermodelled processes using mismatched hidden markov model test filters

J James, JJ Ford, TL Molloy

IEEE Control Systems Letters | Institute of Electrical and Electronics Engineers | Published : 2017

Abstract

In this letter, we present a change detection approach for dependent processes based on the output of a mismatched hidden Markov model (HMM) test filter (i.e., an HMM filter applied to observations not generated by its model). The presented approach is intended to be suitable for dependent processes that are significantly undermodelled in the sense that their conditional densities are not known, are too complex, or are otherwise unsuitable for existing change detection techniques. We establish a description of a mismatched HMM test filter’s output when it is applied to sequences generated by a general dependent process. This description is used to motivate the proposal of a novel change dete..

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