A Two-Level Distributed Multiple Hypothesis Decision System

E. Drakopoulos; J. J. Chao; C. C. Lee

doi:10.1109/9.119643

A Two-Level Distributed Multiple Hypothesis Decision System

E. Drakopoulos, J. J. Chao, C. C. Lee

Electrical and Computer Engineering

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

5 Scopus citations

Abstract

A two-level distributed decision system consisting of a number of local decision makers (LDM's) connected to a global decision maker (GDM) is considered. The LDM's share a common M-hypothesis testing problem, have their own observations independent of each other, and employ likelihood ratios for their decision-making. Each LDM transmits its inference to the GDM where the final decision is derived. The local inferences consist of the ranking of the candidate hypotheses and a degree of confidence based on likelihood ratios. Using a maximum distance criterion, the optimum confidence-based subpartitioning of local decision space is studied. It is shown that the presented system could greatly outperform the one where each LDM provides a single hypothesis hard decision and perform nearly as well as the optimum centralized system.

Original language	English (US)
Pages (from-to)	380-384
Number of pages	5
Journal	IEEE Transactions on Automatic Control
Volume	37
Issue number	3
DOIs	https://doi.org/10.1109/9.119643
State	Published - Mar 1992

ASJC Scopus subject areas

Control and Systems Engineering
Computer Science Applications
Electrical and Electronic Engineering

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A Two-Level Distributed Multiple Hypothesis Decision System

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