In this paper we are going to describe the steps that conform a novel approach for representation of multidimensional datasets through the proposed Framework nD-EVM/Kohonen. In this sense two phases are going to be taken in account: 1) the application of 1-Dimensional Kohonen Self-Organizing Maps (1D-KSOMs) in order to achieve (n-1)D hypervoxelizations' segmentations, n ≥ 2, taking in account t...

Recent studies have shown that the Gibbs density function is a good model for visual patterns and that its parameters can be learned from pattern category training data by a gradient algorithm optimizing a constrained entropy criterion. These studies represented each pattern category by a single density. However, the patterns in a category can be so complex as to require a representation spread...

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This paper discusses a methodology to manage wireless sensor networks (WSN) with self-organising feature maps, using co-operative Extended Kohonen Maps (EKMs). EKMs have been successfully demonstrated in other machine-learning contexts such as learning sensori-motor control and feedback tasks. Through a quantitative analysis of the algorithmic process, an indirect-mapping EKM can self-organise ...

This work describes the utilization of the inherent parallelism of commonly available hardware graphics accelerators for the realization of the Kohonen feature map. The result is an essential reduction of computing time compared to standard software implementations.