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Neural Network Learning Using Entropy Cycle

Neural Network Learning Using Entropy Cycle

Knowledge and Information Systems, 2000
Abstract
.   In this paper, an additional entropy penalty term is used to steer the direction of the hidden node's activation in the process of learning. A state with minimum entropy means that most nodes are operating in the non-linear zones (i.e. saturation zones) near the extreme ends of the Sigmoid curve. As the training proceeds, redundant hidden nodes' activations are

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