Sequential detection of transient changes in stochastic systems under a sampling constraint

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Abstract

The problem of detecting a transient change in distribution of a discrete time series is investigated when there is a constraint on the number of observed samples. Under a minimax setting where the change time is unknown, the objective is to design a statistical test that minimizes a measure of worst case delay under a constraint on the average time to false alarm as well as a constraint on the sampling rate. Leveraging the results in the non-transient setting, it is shown that under full sampling there exists an asymptotic threshold on the minimum duration of a change that can be detected reliably with such false alarm constrained tests. Next, given a transient change with duration above this asymptotic threshold, the smallest sampling rate for which the change can be detected as efficiently as under full sampling is characterized asymptotically.

Original languageEnglish
Title of host publicationProceedings - 2015 IEEE International Symposium on Information Theory, ISIT 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages156-160
Number of pages5
ISBN (Electronic)9781467377041
DOIs
Publication statusPublished - 28 Sept 2015
EventIEEE International Symposium on Information Theory, ISIT 2015 - Hong Kong, Hong Kong
Duration: 14 Jun 201519 Jun 2015

Publication series

NameIEEE International Symposium on Information Theory - Proceedings
Volume2015-June
ISSN (Print)2157-8095

Conference

ConferenceIEEE International Symposium on Information Theory, ISIT 2015
Country/TerritoryHong Kong
CityHong Kong
Period14/06/1519/06/15

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