An unsupervised training connectionist network with lateral inhibition
A new architecture for unsupervised learning is proposed. The topology, activation rules, and training algorithm are presented and a specific training base is used to prove the advantages of this type of network. The training patterns are from chess playing, but there are several other applications for this kind of system, and a specific one is proposed without going into details. Experimental results emphasize the performances of the network training.
KeywordsLateral Inhibition Input Pattern Training Base Pattern Separation Training Epoch
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