Adaptation in natural and artificial systems
Adaptation in natural and artificial systems
Distributed Detection and Data Fusion
Distributed Detection and Data Fusion
Fusion in sensor networks with communication constraints
Proceedings of the 3rd international symposium on Information processing in sensor networks
Decentralized detection in sensor networks
IEEE Transactions on Signal Processing
A survey of communication/networking in Smart Grids
Future Generation Computer Systems
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In this paper, we use a novel Parallel Genetic Algorithm (PGA) approach to simultaneously optimise both the fusion rule and the local decision rules of a decentralised sensor network with correlated observations. The optimisation is performed with respect to the probability of error at the fusion centre. We show that our algorithm converges to a majority-like fusion rule irrespective of the degree of correlation and that the local decision rules play a key role in determining the performance of the overall system. By fixing the fusion rule and optimising only the local rules, we demonstrate that systems having different fusion rules can all provide similar performance if the local rules are chosen appropriately. We also show that the performance of the system degrades with increase in the correlation between the observations.