並列摘要
GreyART network is a kind of hybrid network that incorporates grey relational analysis into adaptive resonant theory (ART). In this study, the learning process of GreyART network is applied to construct the structure of cerebellar model articulation controller (CMAC) to form a GreyART-type CMAC network. The proposed updating rule is in an unsupervised manner as the ART or the GreyART network, and could equally distribute the learning information into the association memory locations as the CMAC network. If the winner fails a vigilance test, a new state is created; otherwise, the memory contents corresponding to the winner are updated according to the learning information. Simulation results demonstrate the effectiveness and feasibility of the GreyART-type CMAC network in solving the Iris dataset.
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