Quickest search over correlated sequences with model uncertainty

Javad Heydari, Ali Tajer, H. Vincent Poor

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

Abstract

An ordered set of data sequences is given where, broadly, the data sequences are categorized into normal and abnormal ones. The normal sequences consist of random variables generated according to a known distribution, while there exist uncertainties about the distributions of the abnormal sequences. Moreover, the generations of different sequences are correlated, induced by an underlying physical coupling, where a sequence being normal or abnormal depends on the status of the rest of the sequences according to a known dependency kernel. The objective is to design the quickest sequential and data-adaptive sampling procedure for identifying one abnormal sequence. This quickest search strategy strikes a balance between the quality and agility of the search process, as two opposing figures of merit. This paper characterizes the sampling and search strategy. Motivated by the fact that full characterization of such strategies can become computationally prohibitive, this paper also proposes asymptotically optimal sampling and search strategies that are computationally efficient.

Original languageEnglish (US)
Title of host publication2016 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2016 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages4284-4287
Number of pages4
ISBN (Electronic)9781479999880
DOIs
StatePublished - May 18 2016
Event41st IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2016 - Shanghai, China
Duration: Mar 20 2016Mar 25 2016

Publication series

NameICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Volume2016-May
ISSN (Print)1520-6149

Other

Other41st IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2016
CountryChina
CityShanghai
Period3/20/163/25/16

All Science Journal Classification (ASJC) codes

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering

Keywords

  • Quickest search
  • correlated sequences
  • model uncertainty
  • stopping time

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