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    Abstract:

    A geometrical representation of M-P model is firstly introduced, by which the training problem of neural networks may be transformed into the covering problem of a point set. According to this, the geometrical algorithm of neural network training is analyzed. The algorithm may be used for constructing very complicated classifying boundary, but it has higher time complexity. So a fuzzy classifier based on the combination of the covering approach and fuzzy set theory is proposed. The classifier can improve the speed of training and decrease the number of covering sphere-neighborhoods, i.e., decrease the number of hidden nodes of neural networks. The fuzzy set based approach may also provide multi-choices for pattern recognition problems of large scale. Recognition of 700 handwritten Chinese characters is used to test the performance of the approach and the results are promising.

    Reference
    [1]Zhang L, Zhang B. A geometrical representation of McCulloch-Pitts neural model and its applications. IEEE Transactions on Neural Networks, 1999,10(4):925~929.
    [2]Wu MR. The research on classifier design for pattern recognition problems of large scale . Beijing: Tsinghua University, 2001 (in Chinese with English Abstract).
    [3]Yang TN, Wang SD. Fuzzy auto-associative neural networks for principal component extraction of noisy data. IEEE Transactions on Neural Networks, 2000,11(3):808~810.
    [4]Zhang D, Pal SK. A fuzzy clustering neural networks (FCNs) system design methodology. IEEE Transactions on Neural Networks, 2000,11(5):1174~1177.
    [5]Ma SP, Xia Y, Zhu XY. Handwritten Chinese characters recognizing based on fuzzy directional line element feature. Journal of Tsinghua University (Science and Technology), 1997,37(3):42~45 (in Chinese with English Abstract).
    [6]吴鸣锐.大规模模式识别问题的分类器设计研究[博士学位论文].北京:清华大学,2001.
    [7]马少平,夏莹,朱小燕.基于模糊方向线素特征的手写体汉字识别.清华大学学报(科学与技术),1997,37(3):42~45.
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叶少珍,张钹,吴鸣锐,郑文波.一种基于神经网络覆盖构造法的模糊分类器.软件学报,2003,14(3):429-434

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History
  • Received:October 08,2001
  • Revised:May 13,2002
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