Patent ID: 6505181
Filing Date: 2003-01-07
Classification: G06K,G06N

Abstract:
A system for classifying data vectors into at least one of a plurality of categories respectively defined by stored vector representations which have been determined by a training process, the system comprising a plurality of interconnected processing elements which, for implementing the training process, include:input means for receiving input training vectors; storage means for storing vector representations of the categories; calculating means for calculating a measure of similarity between an input vector and the stored representations for each category; and means for selecting stored vector representations and then modifying the selected stored vector representations so as to re-define the categories on an iterative basis during the training process; wherein the selecting and modifying means comprises for the processing elements of each category:means for recording a plurality of different measures of learning for the category based on previous modifications to the stored vector representation of that category with respect to the input vectors which have been received by the system; means for combining said recorded measures of learning to form an activation value for the category; means for evaluating a category strength value from said activation value and the respective measure of similarity; and means for receiving the category strength values from the processing elements of other categories in the system and deciding, based upon comparative category strengths, whether or not the selected category representation should be modified.