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In order to improve the generalization ability of feed-forward neural networks, a new objective function of learning procedure for training single hidden layer network is proposed. This objective function is composed of two information entropy, one is the cross entropy as the main optimization term and the other is the fuzzy entropy as the regularization term. In this paper, we are fused the concept...
In this paper we present the results of the first experiments in the investigation of automatically adjusting the learning parameters of an EFuNN. This work in part addresses previous work which speculated that this evolving connectionist system could be further developed with a view to either reducing the overall number of learning parameters or having them adjusted automatically. One of these areas...
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