IDENTIFYING/LEARNING METHOD OF PAPER SHEETS USING COMPETITIVE NEURAL NETWORK

摘要

PROBLEM TO BE SOLVED: To make improvable the identification ability of paper sheets by controlling the number of neurons on the basis of the recognized result and reliability evaluation with respect to learning data. SOLUTION: Sampled paper sheet data are defined as data for learning, data preprocessing is performed to these data (S10), the coefficient of coupling is initialized (S20) and LVQ(Learning Vector Quantization) is executed (S30). When initializing the coefficient of coupling, the average value of input data corresponding to respective neurons is used. By learning the coefficient of coupling, a neural network is constructed, a threshold is prepared corresponding to the learning data (S40) and a neuron not to be ignited is excluded (S50). Next, the evaluation of the learning data and the check of neuron addition are performed (S60 and S70) and it is discriminated whether a neuron is added or not (S80). When no neuron is added, the threshold is expanded (S90). When a neuron is added, operation is returned to S30.