FNN MODEL FOR MULTI-FONT CHARACTER RECOGNITION
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TP391.41 TP18

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    Abstract:

    A novelfuzzy neuralnetw ork (FNN) m odelform ulti-fontcharacterrecognition w as presented, w hich can efficiently process the fuzzy pattern classification problem . This FNN m odelis built by fuzzifying the input layer, output layer and the training algorithm ofa conventionalm ultilayer perceptron (MLP). The sim ulation w ith a lot of m ulti-font character sam ples show s thatthe FNN presented here can geta high recognition rate, and has low sensitivity for different character fonts in com parison w ith classical MLP.Also, this FNN is proved to have a good robustness.

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WANG Lei, QI Fei-Hu. FNN MODEL FOR MULTI-FONT CHARACTER RECOGNITION[J]. Journal of Infrared and Millimeter Waves,1999,18(5):412~416

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