• Journal of Infrared and Millimeter Waves
  • Vol. 24, Issue 1, 15 (2005)
[in Chinese]1、2 and [in Chinese]2、3
Author Affiliations
  • 1[in Chinese]
  • 2[in Chinese]
  • 3[in Chinese]
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    DOI: Cite this Article
    [in Chinese], [in Chinese]. METHOD FOR IMPROVING CLASSIFICATION PERFORMANCE OF NEURAL NETWORK BASED ON FUZZY INPUT AND NETWORK INVERSION[J]. Journal of Infrared and Millimeter Waves, 2005, 24(1): 15 Copy Citation Text show less
    References

    [1] Ishibuchi H, Kwon K, Tanaka H, A learning algorithm of fuzzy neural networks with triangular fuzzy weights [J],Fuzzy Sets and Systems, 1995, 71: 277-293.

    [2] Hayashi Y, Fuzzy neural network with fuzzy signals and weights [J], International Journal of Intelligent Systems,1993, 8: 527-537.

    [3] Ishibuchi H, Nii M, Fuzzification of input vectors for improving the generalization ability of neural networks [C], In:Proceedings of the International Joint Conference on Neural Networks, Anchorage, Alaska, May 4-9, 1998,2: 1153-1158.

    [4] LI Zhen-Quan, Kecman V, Ichikawa A, Fuzzified neural network based on fuzzy number operation [J], Fuzzy Sets and Systems, 2002, 130:291-304.

    [5] Ishibuchi H, Nii M, Numerical analysis of the learning of fuzzified neural networks from fuzzy if-then rules [J] , Fuzzy Sets and Systems, 2001, 120:281-307.

    [in Chinese], [in Chinese]. METHOD FOR IMPROVING CLASSIFICATION PERFORMANCE OF NEURAL NETWORK BASED ON FUZZY INPUT AND NETWORK INVERSION[J]. Journal of Infrared and Millimeter Waves, 2005, 24(1): 15
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