Self-organizing Maps and Hybrid Information Control Systems

R. Kamimura, T. Kamimura, and O. Uchida (Japan)



In this paper, we propose a new type of information system for self-organization to produce coherent neuron firing pat terns. The new information system is composed of a SOM component and an information maximization component. In the SOM component, the conventional SOM is used to cooperate neurons. In the information maximization component, information in competitive units is increased as much as possible. The component plays a role to accentuate an activation pattern obtained by the SOM component. We apply the new method to medical data analysis. Experimental results confirm that firing patterns obtained by the conventional SOM are reinforced and become clearer by the information maximization component.

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