Comparison of Five Algorithms for Recognizing Serlal Number of Rmb Banknote
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    Abstract:

    To investigate the performance of different neural network algorithms in identifying serial number of RMB banknote, the training speed, recognizing speed and rate, and ability of anti-noise of five neural network algorithms, including the discrete Hopfield neural network, BP neural network, PNN neural network, GRNN neural network and SVM neural network, are studied. The simulation results show that amongst the five algorithms, BP performs worst, followed by SVM and Hopfield, with PNN and GRNN performs best, not only gives the higher recognition rate, shorter training and recognition time, but also is more robust to noise.

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刘小波,崔桂华,李长军,钱祥忠,严旭.五种人民币序列号识别算法抗噪能力比较.计算机系统应用,2016,25(8):29-34

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  • Received:December 16,2015
  • Revised:January 21,2016
  • Online: August 16,2016
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