Joint detection and identification of an unobservable change in the distribution of a random sequence

Savas Dayanik, Christian Goulding, H. Vincent Poor

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

3 Scopus citations

Abstract

This paper examines the joint problem of detection and identification of a sudden and unobservable change in the probability distribution function (pdf) of a sequence of independent and identically distributed (i.i.d.) random variables to one of finitely many alternative pdf's. The objective is quick detection of the change and accurate inference of the ensuing pdf. Following a Bayesian approach, a new sequential decision strategy for this problem is revealed and is proven optimal. Geometrical properties of this strategy are demonstrated via numerical examples.

Original languageEnglish (US)
Title of host publicationForty-first Annual Conference on Information Sciences and Systems, CISS 2007 - Proceedings
Pages68-73
Number of pages6
DOIs
StatePublished - Dec 1 2007
Event41st Annual Conference on Information Sciences and Systems, CISS 2007 - Baltimore, MD, United States
Duration: Mar 14 2007Mar 16 2007

Publication series

NameForty-first Annual Conference on Information Sciences and Systems, CISS 2007 - Proceedings

Other

Other41st Annual Conference on Information Sciences and Systems, CISS 2007
CountryUnited States
CityBaltimore, MD
Period3/14/073/16/07

All Science Journal Classification (ASJC) codes

  • Computer Science(all)

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