A Bayesian Approach to Sequential Change Detection and Isolation Problems

Jie Chen; Wenyi Zhang; H. Vincent Poor

doi:10.1109/TIT.2020.3042878

A Bayesian Approach to Sequential Change Detection and Isolation Problems

Jie Chen, Wenyi Zhang, H. Vincent Poor

Research output: Contribution to journal › Article › peer-review

4 Scopus citations

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)
Article number	9284581
Pages (from-to)	1796-1803
Number of pages	8
Journal	IEEE Transactions on Information Theory
Volume	67
Issue number	3
DOIs	https://doi.org/10.1109/TIT.2020.3042878
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

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10.1109/TIT.2020.3042878

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AU - Poor, H. Vincent

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AB - 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.

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KW - decision procedures

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A Bayesian Approach to Sequential Change Detection and Isolation Problems

Abstract

All Science Journal Classification (ASJC) codes

Keywords

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