Fuzzy parameter adaptation in neural systems

The general structure of a neuro-fuzzy controller applicable to many diverse neural systems is presented. As an example, fuzzy control of the backpropagation training technique is considered for multilayer perceptrons, where significant speedup in training was observed. Fuzzy control of the number of classes in an ART 1 classifier is also considered. This can be advantageous in situations where there is prior knowledge of the number of classes into which one wishes to classify the input data