The self-organizing map’s unsupervised clustering property, is known for classifying high dimensional data sets into clusters that have similar features. Using this property and arranging self-organizing maps into hierarchies, we demonstrate in this paper that legacy code can be potentially broken down into suggested classes using hierarchical self-organizing maps. This is in conjunction with i...

An overview on the usage of emergent self organizing maps is given. U-Maps visualize the distance structures of high dimensional data sets. P-Maps show their density structures and U*-Maps combine the advantages of the mentioned maps to a visualization suitable to detect nontrivial cluster structures. A concise summary on the usage of Emergent Self-organizing Maps (ESOM) for data mining is give...

This paper shows that a system with two link arm can obtain arm reaching movement to a target object by combination of reinforcement learning and dynamic self organizing map. Proposed model in this paper present state and action space of reinforcement learning with dynamis self organizing maps. Because these spaces are continuous. proposed model uses two dynamic self-organizing maps (DSOM) to e...