Patent ID: 6016384
Filing Date: 2000-01-18
Classification: G06K,G06N

Abstract:
A learning method for developing patterns to be incorporated into a neural network of the multi-layer perceptron type intended to recognize a set of sample patterns in which back-propagation is relied upon to change network weights during training, wherein convergence as between input patterns to be recognized and existing patterns of the neural network is speeded up, said learning method comprising:increasing the learning capability of the neural network in a first stage by:extracting an initial set of patterns as a selected subset from a set of patterns making up the complete learning set of patterns to be processed during a training phase, and providing the initial set of patterns to the neural network,operating on the complete learning set of patterns including the initial set of patterns as provided to the neural network in accordance with a learning program,progressively adding new patterns to the initial set of patterns as the new patterns are recognized by the neural network,reiterating the operation of the learning program on the complete learning set of patterns,further adding new patterns as recognized to the subset of the previously recognized patterns as defined by the initial set of patterns and all new recognized patterns as added thereto, andrepeating the iteration of the operation of the learning program and the adding of new patterns as recognized to the subset of the previously recognized patterns until no new patterns are recognized by the neural network in completing the first stage of the learning method;increasing the learning capability of the neural network in a second stage by progressively adding previously unrecognized patterns to the subset of previously recognized patterns as the previously unrecognized patterns are recognized; andincreasing the learning capability of the neural network in a third stage by progressively corrupting unrecognized patterns in the assimilation of such unrecognized patterns with previously recognized patterns until the corrupted unrecognized patterns are recognized and then progressively adding the corrupted unrecognized patterns as recognized to the subset of previously recognized patterns.