Abstract
In this paper, a general method to train binary multilayer perceptrons is presented. This method is based on the use of fuzzy rules to upgrade the weights as well as to state the desired output of the neurons of the hidden layers. The version for networks with one hidden layer and one output neuron is carefully described and illustrated with examples.
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