—In this paper, we address the problem of establishing full connectivity and satisfying required traffic capacity between disconnected clusters in large wireless ad-hoc ground n...
Density-based clustering has the advantages for (i) allowing arbitrary shape of cluster and (ii) not requiring the number of clusters as input. However, when clusters touch each o...
— Network clustering enables us to view a complex network at the macro level, by grouping its nodes into units whose characteristics and interrelationships are easier to analyze ...
This paper presents a method of generating Mercer Kernels from an ensemble of probabilistic mixture models, where each mixture model is generated from a Bayesian mixture density e...
We introduce a new learning algorithm for topographic map formation of Edgeworth-expanded Gaussian activation kernels. In order to avoid the rapid increase in kernel parameters, a...