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《Computer Technology and Development》 2007-01
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Recognition of Handwritten Numerals with Grouped BP Net Based on Structural Features

GENG Xi-wei,ZHANG Meng,SHEN Jian-jing(PLA Information Engineering University,Zhengzhou 450001,China)  
Handwritten numeral recognition has important use value.It is a great advancement to use multi-layer BP network to identify numbers write by hand.But it has problems to use single BP network to identify.Combines BP network with the character of number structure,then a new method of grouped BP net based on structural features is proposed to classify handwritten numbers.Point and circle features cell are extracted and combined.Then,BP net is grouped based on some structural features.The system recognizes number by grouped BP neural network,therefore it obtains better effect.Finally,select the handwriting of 500 people from 0 to 9,using arithmetic to recognize(3000 swatches for training,2000 for testing).After net constringed,the distinguishing rate is over 96%.
【CateGory Index】: TP183;TP391.4
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