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Proceedings Paper

Some properties of optimal thresholds in decentralized detection
Author(s): William W. Irving; John N. Tsitsiklis
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Paper Abstract

A decentralized Bayesian hypothesis testing problem is considered. It is analytically demonstrated that for the binary hypothesis problem, when there are two sensors with statistically independent Gaussian-distributed observations (conditioned on the true hypothesis), there is no loss in optimality in using the same decision rule at both sensors. Also, a multiple hypothesis problem is considered; some structure is analytically established for a optimal set of decision rules.

Paper Details

Date Published: 30 April 1992
PDF: 9 pages
Proc. SPIE 1611, Sensor Fusion IV: Control Paradigms and Data Structures, (30 April 1992); doi: 10.1117/12.57943
Show Author Affiliations
William W. Irving, Massachusetts Institute of Technology (United States)
John N. Tsitsiklis, Massachusetts Institute of Technology (United States)

Published in SPIE Proceedings Vol. 1611:
Sensor Fusion IV: Control Paradigms and Data Structures
Paul S. Schenker, Editor(s)

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