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Effects of noise in training patterns on the memory capacity of the fully connected binary Hopfield neural network: mean-field theory and simulations

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1 Author(s)
L. Wang ; Dept. of Comput. & Math., Deakin Univ., Clayton, Vic., Australia

We show that the memory capacity of the fully connected binary Hopfield network is significantly reduced by a small amount of noise in training patterns. Our analytical results obtained with the mean field method are supported by extensive computer simulations

Published in:

IEEE Transactions on Neural Networks  (Volume:9 ,  Issue: 4 )