Interactive fusion in distributed detection: Architecture and performance analysis

Earnest Akofor, Biao Chen

Research output: Chapter in Book/Entry/PoemConference contribution

5 Scopus citations

Abstract

Within the Neyman-Pearson framework we investigate the effect of feedback in two-sensor tandem fusion networks with conditionally independent observations. While there is noticeable improvement in performance of the fixed sample size Neyman-Pearson (NP) test, it is shown that feedback has no effect on the asymptotic performance characterized by the Kullback-Leibler (KL) distance. The result can be extended to an interactive fusion system where the fusion center and the sensor may undergo multiple steps of interactions.

Original languageEnglish (US)
Title of host publication2013 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2013 - Proceedings
Pages4261-4265
Number of pages5
DOIs
StatePublished - Oct 18 2013
Event2013 38th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2013 - Vancouver, BC, Canada
Duration: May 26 2013May 31 2013

Publication series

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

Other

Other2013 38th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2013
Country/TerritoryCanada
CityVancouver, BC
Period5/26/135/31/13

Keywords

  • Distributed detection
  • Interactive fusion
  • Kullback-Leibler distance
  • Neyman-Pearson test

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering

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