Automatic fusion and splitting of artificial neural elements in optimizing the network size
説明
A three-layered neural network that optimally self-adjusts the number of hidden layer units is proposed. The network combines two techniques: (1) unit fusion which enables an efficient pruning of the redundant units: and (2) linear transformations applied to the chosen hidden layer unit pair output and a modified backpropagation training rule for gradual fusion to reduce pruning shocks. The network was applied to a character recognition problem and it adjusted itself to a minimal configuration at high rate. >
収録刊行物
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- Conference Proceedings 1991 IEEE International Conference on Systems, Man, and Cybernetics
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Conference Proceedings 1991 IEEE International Conference on Systems, Man, and Cybernetics 1633-1638, 2002-12-09
IEEE