Method for speeding up the convergence of the back-propagation algorithm applied to realize the learning process in a neural network of the multilayer perceptron type

摘要

A method for speeding up the convergence of the back- propagation algorithm applied to realize the learning process in a neural network of the multilayer perceptron type intended for instance to recognize a set of samples. The method comprises a first stage based upon the elementary concept of progressively increasing the capability for learning of the network by progressively adding new samples as they are recognized by the network to a starting set of learning samples; a second stage based upon the concept of progressively increasing the learning capabilities of the network by progressively adding not previously recognized samples; and a third stage based upon the concept of progressively increasing the learning capabilities of the network by progressive corruption in the meaning of the assimilation between recognized samples and not recognized samples and their subsequent exposure to the network.