Multi-Stream Quickest Detection with Unknown Post-Change Parameters Under Sampling Control

The multi-stream quickest detection problem with unknown post-change parameters is studied under the sampling control constraint, where there are M local processes in a system but one is only able to take observations from one of these M local processes at each time instant. The objective is to rais...

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Bibliographic Details
Published in2021 IEEE International Symposium on Information Theory (ISIT) pp. 112 - 117
Main Authors Xu, Qunzhi, Mei, Yajun
Format Conference Proceeding
LanguageEnglish
Published IEEE 12.07.2021
Subjects
Asymptotic optimality
change-point detection
Delays
Detection algorithms
Information theory
Process control
quickest detection
sampling control
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Summary:The multi-stream quickest detection problem with unknown post-change parameters is studied under the sampling control constraint, where there are M local processes in a system but one is only able to take observations from one of these M local processes at each time instant. The objective is to raise a correct alarm as quickly as possible once the change occurs subject to both false alarm and sampling control constraints. We propose an efficient myopic-sampling-based quickest detection algorithm under sampling control constraint, and show it is asymptotically optimal in the sense of minimizing the detection delay under our context when the number M of processes is fixed. Simulation studies are conducted to validate our theoretical results.
DOI:10.1109/ISIT45174.2021.9517836