A learning algorithm for a self-organizing map (SOM) is proposed. The algorithm accelerates information processing due to the rational choice as the learning rate parameter, and can work when the number of clusters is unknown, as well as when the clusters are overlapping. This is achieved via the introduction of fuzzy inference that determines the level of membership of the classified pattern to each of the available classes.
clustering, self-training, competition, synaptic adaptation, co-operation, unclear conclusion
"Neironnaia set T. Kokhonena s nechetkym vыvodom y alhorytm ee samoobuchenyia" ,
Scientific Works of Kharkiv National Air Force University,