A Two-Level Distributed Multiple Hypothesis Decision System

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

Research output: Contribution to journalArticlepeer-review

5 Scopus citations


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 languageEnglish (US)
Pages (from-to)380-384
Number of pages5
JournalIEEE Transactions on Automatic Control
Issue number3
StatePublished - Mar 1992

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Computer Science Applications
  • Electrical and Electronic Engineering


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