Quickest change detection under transient dynamics

Georgios Rovatsos, Shaofeng Zou, Venugopal V. Veeravalli

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

Abstract

The problem of transient quickest change detection (QCD) is studied, in which the change from the initial to the final phase does not happen instantaneously, but after a series of cascading transient phases of finite durations, each one corresponding to a different probability distribution. The goal is to design a stopping rule to detect the change as quickly as possible, subject to false alarm constraints. In previous work, the D-CuSum algorithm was proposed for such a QCD problem. The D-CuSum does not incorporate any prior statistical information about the durations of the transient periods. In this work, we develop an algorithm, the D-S-R algorithm, which incorporates geometric priors on the durations of the transient periods. We compare the D-CuSum and D-S-R algorithms in numerical examples to develop some insights about the role of the prior on the transient durations on the performance.

Original languageEnglish (US)
Title of host publication2017 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2017 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages4785-4789
Number of pages5
ISBN (Electronic)9781509041176
DOIs
StatePublished - Jun 16 2017
Event2017 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2017 - New Orleans, United States
Duration: Mar 5 2017Mar 9 2017

Publication series

NameICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
ISSN (Print)1520-6149

Other

Other2017 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2017
CountryUnited States
CityNew Orleans
Period3/5/173/9/17

Keywords

  • Bayesian analysis
  • dynamic CuSum
  • dynamic Shiryaev-Roberts
  • quickest change detection
  • transient dynamics

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering

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