The good, bad and ugly: distributed detection of a known signal in dependent Gaussian noise
IEEE Transactions on Signal Processing
On some unresolved issues in finding optimum distributed detection schemes
IEEE Transactions on Signal Processing
Asymptotic performance of a distributed detection system incorrelated Gaussian noise
IEEE Transactions on Signal Processing
A Bayesian sampling approach to decision fusion using hierarchicalmodels
IEEE Transactions on Signal Processing
Distributed signal detection under the Neyman-Pearson criterion
IEEE Transactions on Information Theory
Adaptive Counting Rule for Cooperative Spectrum Sensing Under Correlated Environments
Wireless Personal Communications: An International Journal
Information Sciences: an International Journal
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We have considered in this paper the conditions for the equivalence of the counting rule and the likelihood ratio test when implementing the fusion rule of decisions corresponding to identically operated correlated sensors. A simple model of correlation, defined by two correlation indices, one for every hypothesis, has been considered. A main conclusion is that for properly operating sensors, the counting rule is almost a UMP test in the correlation indices.