Neural assembly generation by selective connection weight updating

In this paper, a neural network model, which learns symbols is introduced. VSF-Network (Vibration Synchronizing Function Network) is a hybrid neural network combining a chaos neural network with a hierarchical network. It has an ability for a incremental learning of patters by abstracting input data. VSF-Network finds unknown elements in data based on clusters generated by chaos neurons. VSF-Network generates sub-networks while it learns new patterns based on the information about the clusters. When a combination of learned patterns is presented, VSF-network recognizes them by combining its sub-networks. In this paper, an incremental learning model to examine the dynamics of VSF-network is introduced. The performances of the incremental learning by VSF-network are shown through the two tasks and the discussion about the combination form of the sub-networks generated by VSF-Network.