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Tandem Distributed Detection with Conditionally Dependent Observations
15th International Conference on Information Fusion
  • Pengfei Yang, Syracuse University
  • Biao Chen, Syracuse University
  • Hao Chen, Boise State University
  • Pramod K. Varshney, Syracuse University
Document Type
Conference Proceeding
Publication Date
7-9-2012
Abstract
This paper deals with distributed detection using a tandem network with conditionally dependent observations. Our approach utilizes a recently proposed hierarchical conditional independence model where a hidden variable is introduced and induces conditional independence among sensor observations. If the hidden variable is discrete, optimal local decision rules are reminiscent that of the conditional independence case. For continuous scalar hidden variable, similar results can be obtained when additional monotonicity conditions are imposed.
Citation Information
Pengfei Yang, Biao Chen, Hao Chen and Pramod K. Varshney. "Tandem Distributed Detection with Conditionally Dependent Observations" 15th International Conference on Information Fusion (2012)
Available at: http://works.bepress.com/hao_chen/19/