Fuzzy logic based modification system for the learning rate in backpropagation
This paper proposes a fuzzy logic modification system to the standard backpropagation algorithm, with respect to the learning rate parameter. Instead of relying on the proper choice of the fixed learning rate parameter, for which no explicit mathematical model exists, a fuzzy system controller is used to dynamically adjust the learning rate based upon a set of problem domain heuristics. The objective is to speed up training time while also providing a more stable convergence. Character recognition application is used to demonstrate the usefulness of the proposed system.
learning rate backpropagation character recognition fuzzy logic controller fuzzy inference system neural networks fuzzy algorithms fuzzy rule base fuzzy learning rate adaptive learning rate