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In this paper, we develop a new change detection algorithm for detecting achange in the Markov kernel over a metric space in which the post-change kernelis unknown. Under the assumption that the pre- and post-change Markov kernel isuniformly ergodic, we derive an upper bound on the mean delay and a lower boundon the mean time between false alarms. A numerical simulation is provided todemonstrate the effectiveness of our method.

Change Detection of Markov Kernels with Unknown Pre and Post Change Kernel