This paper deals with clustering of spatially distributed data using wireless sensor networks. A distributed low-complexity clustering algorithm is developed that requires one-hop...
Pedro A. Forero, Alfonso Cano, Georgios B. Giannak...
The average consensus in wireless sensor networks is achieved under assumptions of symmetric or balanced topology at every time instant. However, communication and/or node failure...
In this paper, we present a novel entropy estimator for a given set of samples drawn from an unknown probability density function (PDF). Counter to other entropy estimators, the e...
Exploiting prior knowledge, we use Bayesian estimation to localize a source heard by a fixed sensor network. The method has two main aspects: Firstly, the probability density fun...
This paper introduces a distributed auxiliary particle filter for target tracking in sensor networks. Nodes maintain a shared particle filter by coming to a consensus about the ...