Sequential Change Detection of a Correlation Structure under a Sampling Constraint

Anamitra Chaudhuri, Georgios Fellouris, Ali Tajer

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The problem of sequentially detecting a change in the correlation structure of multiple Gaussian information sources is considered when it is possible to sample only two of them at each time instance. It is assumed that all sources are initially independent and that at least two of them become positively correlated after the change. The problem is to stop sampling as quickly as possible after the change, while controlling the false alarm rate and without assuming any prior information on the number of sources that become correlated. A joint sampling and change-detection rule is proposed and is shown to achieve the smallest possible worst-case conditional expected detection delay among all processes that satisfy the same constraints, to a first order approximation as the false alarm rate goes to 0, for any possible number of post-change correlated sources.

Original languageEnglish (US)
Title of host publication2021 IEEE International Symposium on Information Theory, ISIT 2021 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages605-610
Number of pages6
ISBN (Electronic)9781538682098
DOIs
StatePublished - Jul 12 2021
Event2021 IEEE International Symposium on Information Theory, ISIT 2021 - Virtual, Melbourne, Australia
Duration: Jul 12 2021Jul 20 2021

Publication series

NameIEEE International Symposium on Information Theory - Proceedings
Volume2021-July
ISSN (Print)2157-8095

Conference

Conference2021 IEEE International Symposium on Information Theory, ISIT 2021
Country/TerritoryAustralia
CityVirtual, Melbourne
Period7/12/217/20/21

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Information Systems
  • Modeling and Simulation
  • Applied Mathematics

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