An Information Theoretic Approach to the Distributed Detection Problem

Imad Y. Hoballah; Pramod K. Varshney

doi:10.1109/18.42216

An Information Theoretic Approach to the Distributed Detection Problem

Imad Y. Hoballah, Pramod K. Varshney

Department of Electrical Engineering & Computer Science

Research output: Contribution to journal › Article › peer-review

61 Scopus citations

Abstract

The distributed detection problem is considered from an information theoretic point of view. An entropy-based cost function is used for system optimization. This cost function maximizes the amount of information transfer between the input and the output. Distributed detection system topologies with and without a fusion center are considered and an optimal fusion rule and optimal decision rules are derived.

Original language	English (US)
Pages (from-to)	988-994
Number of pages	7
Journal	IEEE Transactions on Information Theory
Volume	35
Issue number	5
DOIs	https://doi.org/10.1109/18.42216
State	Published - Sep 1989

ASJC Scopus subject areas

Information Systems
Computer Science Applications
Library and Information Sciences

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10.1109/18.42216

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abstract = "The distributed detection problem is considered from an information theoretic point of view. An entropy-based cost function is used for system optimization. This cost function maximizes the amount of information transfer between the input and the output. Distributed detection system topologies with and without a fusion center are considered and an optimal fusion rule and optimal decision rules are derived.",

author = "Hoballah, {Imad Y.} and Varshney, {Pramod K.}",

note = "Funding Information: Manuscript received December 1, 1986; revised July 7, 1988. This work was supported by the Rome Air Development Center under Contract F30602-81-C-0169. This paper was presented at the 1986 IEEE Intema-tional Symposium on Information Theory, Ann Arbor, MI, October 1986.",

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N2 - The distributed detection problem is considered from an information theoretic point of view. An entropy-based cost function is used for system optimization. This cost function maximizes the amount of information transfer between the input and the output. Distributed detection system topologies with and without a fusion center are considered and an optimal fusion rule and optimal decision rules are derived.

AB - The distributed detection problem is considered from an information theoretic point of view. An entropy-based cost function is used for system optimization. This cost function maximizes the amount of information transfer between the input and the output. Distributed detection system topologies with and without a fusion center are considered and an optimal fusion rule and optimal decision rules are derived.

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An Information Theoretic Approach to the Distributed Detection Problem

Abstract

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