ZHU Xiaoming, WANG Shitong. RESEARCH ON THE LEARNING RULES AND THEIR CONVERGENCE OF MONOLITHIC FUZZY NEURAL NETWORKSJ. Journal of Computer Research and Development, 2001, 38(9): 1057-1060.
Citation:
ZHU Xiaoming, WANG Shitong. RESEARCH ON THE LEARNING RULES AND THEIR CONVERGENCE OF MONOLITHIC FUZZY NEURAL NETWORKSJ. Journal of Computer Research and Development, 2001, 38(9): 1057-1060.
ZHU Xiaoming, WANG Shitong. RESEARCH ON THE LEARNING RULES AND THEIR CONVERGENCE OF MONOLITHIC FUZZY NEURAL NETWORKSJ. Journal of Computer Research and Development, 2001, 38(9): 1057-1060.
Citation:
ZHU Xiaoming, WANG Shitong. RESEARCH ON THE LEARNING RULES AND THEIR CONVERGENCE OF MONOLITHIC FUZZY NEURAL NETWORKSJ. Journal of Computer Research and Development, 2001, 38(9): 1057-1060.
RESEARCH ON THE LEARNING RULES AND THEIR CONVERGENCE OF MONOLITHIC FUZZY NEURAL NETWORKS
J Z Liang presents monolithic fuzzy neural networks （MFNNs） and studies their function approximation capabilities. In this paper, the learning rules of MFNNs are proposed and their convergence properties are studied. The results here show that the learning rules presented are convergent, which provides solid theoretical foundation for MFNNs’ application.
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