A Bayesian Approach to Sequential Change Detection and Isolation Problems

Jie Chen, Wenyi Zhang, H. Vincent Poor

Research output: Contribution to journalArticlepeer-review

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 languageEnglish (US)
Article number9284581
Pages (from-to)1796-1803
Number of pages8
JournalIEEE Transactions on Information Theory
Volume67
Issue number3
DOIs
StatePublished - Mar 2021

All Science Journal Classification (ASJC) codes

  • Information Systems
  • Computer Science Applications
  • Library and Information Sciences

Keywords

  • Asymptotic behavior
  • average detection delay
  • Bayesian change detection
  • change detection and isolation
  • decision procedures

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