Abstract
The problem of sequential change detection and isolation under the Bayesian setting is investigated, where the change point is a random variable with a known distribution. A recursive algorithm is proposed, which utilizes the prior distribution of the change point. We show that the proposed decision procedure is guaranteed to control the false alarm probability and the false isolation probability separately under certain regularity conditions, and it is asymptotically optimal with respect to a Bayesian criterion.
Original language | English (US) |
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Article number | 9284581 |
Pages (from-to) | 1796-1803 |
Number of pages | 8 |
Journal | IEEE Transactions on Information Theory |
Volume | 67 |
Issue number | 3 |
DOIs | |
State | Published - Mar 2021 |
Externally published | Yes |
All Science Journal Classification (ASJC) codes
- Information Systems
- Computer Science Applications
- Library and Information Sciences
Keywords
- Asymptotic behavior
- Bayesian change detection
- average detection delay
- change detection and isolation
- decision procedures