A Hierarchical Extended Kohonen Map (HEKM) learns to associate actions to perceptions under the supervision of a planner: they cooperate to solve path nding problems. We argue for the utility of using the hierarchical version of the KM instead of the \\at" KM. We measure the beneets of cooperative learning due to the interaction of neighboring neurons in the HEKM. We highlight a beneecial side-...

The Kohonen Self Organizing Map (SOM), is a topology preserving map that maps data from higher dimensions onto a (typically) two dimensional grid of lattice points[3]. The aim of Self-Organization is to generate a topology preserving mapping, where the neighborhood relations in the input space are preserved as well as possible, in the neighborhood relations of the units of the map[2]. One of th...

Abstract—Diabetes is considered a lifestyle disease and a well managed self-care plays an important role in the treatment. Clinicians often conduct surveys to understand the self-care behaviours in their patients. In this context, we propose to use Self-Organising Maps (SOM) to explore the survey data for assessing the self-care behaviours in Type-1 diabetic patients. Specifically, SOM is used ...

We transfer the idea of winner relaxing learning from the self-organizing map to the neural gas to enable magnification control independently of the shape of the data distribution.

Time information of the input data is used for evaluating the goodness of the Self-Organizing Map to store and represent temporal feature vector sequences. A new node neighborhood is defined for the map which takes the temporal order of the input samples into account. A connection is created between those two map nodes which are the best-matching units for two successive input samples in time. ...

Currently, there exist many research areas that produce large multivariable datasets that are difficult to visualize in order to extract useful information. Kohonen selforganizing maps have been used successfully in the visualization and analysis of multidimensional data. In this work, a projection technique that compresses multidimensional datasets into two dimensional space using growing self...