Quickest Change Detection and Kullback-Leibler Divergence for Two-State Hidden Markov Models

@article{Fuh2015QuickestCD,
  title={Quickest Change Detection and Kullback-Leibler Divergence for Two-State Hidden Markov Models},
  author={Cheng-Der Fuh and Yajun Mei},
  journal={2015 IEEE International Symposium on Information Theory (ISIT)},
  year={2015},
  pages={141-145}
}
In this paper, the quickest change detection problem is studied in two-state hidden Markov models (HMM), where the vector parameter θ of the HMM changes from θ0 to θ1 at some unknown time, and one wants to detect the true change as quickly as possible while controlling the false alarm rate. It turns out that the generalized likelihood ratio (GLR) scheme, while theoretically straightforward, is generally computationally infeasible for the HMM. To develop efficient but computationally simple… CONTINUE READING

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