Change Detection of Markov Kernels with Unknown Pre and Post Change Kernel
Systems and Control
2024-03-28 v2 Systems and Control
Probability
Machine Learning
Abstract
In this paper, we develop a new change detection algorithm for detecting a change in the Markov kernel over a metric space in which the post-change kernel is unknown. Under the assumption that the pre- and post-change Markov kernel is uniformly ergodic, we derive an upper bound on the mean delay and a lower bound on the mean time between false alarms. A numerical simulation is provided to demonstrate the effectiveness of our method.
Cite
@article{arxiv.2201.11722,
title = {Change Detection of Markov Kernels with Unknown Pre and Post Change Kernel},
author = {Hao Chen and Jiacheng Tang and Abhishek Gupta},
journal= {arXiv preprint arXiv:2201.11722},
year = {2024}
}
Comments
7 pages, 4 figures