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Distributed normalisation input coding to speed up training process of BP-neural network classifier

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2 Author(s)

A coding method, distributed normalisation, is presented to speed up the training process of a back-propagation neural network classifier. In contrast to one-node normalisation coding, the values of the feature variables are distributed over a number of input nodes to increase the representation range of certain parts of each feature variable. A distinct advantage of this coding method is its ability to maintain the generalisation capability of one-node normalisation coding

Published in:

Electronics Letters  (Volume:31 ,  Issue: 15 )