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

Savas Dayanik; Christian Goulding; H. Vincent Poor

doi:10.1109/CISS.2007.4298275

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 proceeding › Conference contribution

4 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 language	English (US)
Title of host publication	Forty-first Annual Conference on Information Sciences and Systems, CISS 2007 - Proceedings
Pages	68-73
Number of pages	6
DOIs	https://doi.org/10.1109/CISS.2007.4298275
State	Published - 2007
Externally published	Yes
Event	41st Annual Conference on Information Sciences and Systems, CISS 2007 - Baltimore, MD, United States Duration: Mar 14 2007 → Mar 16 2007

Publication series

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

Other

Other	41st Annual Conference on Information Sciences and Systems, CISS 2007
Country/Territory	United States
City	Baltimore, MD
Period	3/14/07 → 3/16/07

All Science Journal Classification (ASJC) codes

General Computer Science

Access to Document

10.1109/CISS.2007.4298275

Cite this

Dayanik, S., Goulding, C., & Poor, H. V. (2007). Joint detection and identification of an unobservable change in the distribution of a random sequence. In Forty-first Annual Conference on Information Sciences and Systems, CISS 2007 - Proceedings (pp. 68-73). Article 4298275 (Forty-first Annual Conference on Information Sciences and Systems, CISS 2007 - Proceedings). https://doi.org/10.1109/CISS.2007.4298275

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Dayanik, S, Goulding, C & Poor, HV 2007, Joint detection and identification of an unobservable change in the distribution of a random sequence. in Forty-first Annual Conference on Information Sciences and Systems, CISS 2007 - Proceedings., 4298275, Forty-first Annual Conference on Information Sciences and Systems, CISS 2007 - Proceedings, pp. 68-73, 41st Annual Conference on Information Sciences and Systems, CISS 2007, Baltimore, MD, United States, 3/14/07. https://doi.org/10.1109/CISS.2007.4298275

Joint detection and identification of an unobservable change in the distribution of a random sequence. / Dayanik, Savas; Goulding, Christian; Poor, H. Vincent.
Forty-first Annual Conference on Information Sciences and Systems, CISS 2007 - Proceedings. 2007. p. 68-73 4298275 (Forty-first Annual Conference on Information Sciences and Systems, CISS 2007 - Proceedings).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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AB - 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.

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Dayanik S, Goulding C, Poor HV. Joint detection and identification of an unobservable change in the distribution of a random sequence. In Forty-first Annual Conference on Information Sciences and Systems, CISS 2007 - Proceedings. 2007. p. 68-73. 4298275. (Forty-first Annual Conference on Information Sciences and Systems, CISS 2007 - Proceedings). doi: 10.1109/CISS.2007.4298275

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

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