Optimum Local Decision Rules in a Distributed Detection System with Dependent Observations
Authors
Abstract:
The theory of distributed detection is receiving a lot of attention. A common assumption used in previous studies is the conditional independence of the observations. In this paper, the optimization of local decision rules for distributed detection networks with correlated observations is considered. We focus on presenting the detection theory for parallel distributed detection networks with fixed fusion rules to develop a numeric algorithm based on Neyman-Pearson criterion. Simulation results are 

 presented to demonstrate the efficiency and convergence properties of the algorithm.

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Journal title
volume 25 issue 2
pages 1- 10
publication date 2007-01
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