| Paper ID | D1-S2-T3.3 |
| Paper Title |
Multi-Stream Quickest Detection with Unknown Post-Change Parameters Under Sampling Control |
| Authors |
Qunzhi Xu, Yajun Mei, Georgia Institute of Technology, United States |
| Session |
D1-S2-T3: Quickest Change Detection |
| Chaired Session: |
Monday, 12 July, 22:20 - 22:40 |
| Engagement Session: |
Monday, 12 July, 22:40 - 23:00 |
| Abstract |
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.
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