Fuzzy logic systems are equivalent to feedforward neural networks

被引:5
作者
Li, HX [1 ]
机构
[1] Beijing Normal Univ, Dept Math, Beijing 100875, Peoples R China
来源
SCIENCE IN CHINA SERIES E-TECHNOLOGICAL SCIENCES | 2000年 / 43卷 / 01期
基金
中国国家自然科学基金;
关键词
fuzzy logic systems; neural networks; feedforward neural networks; interpolation representation; rectangle wave neural networks; nonlinear neural networks; linear neural networks;
D O I
10.1007/BF02917136
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Fuzzy logic systems and feedforward neural networks are equivalent in essence. First, interpolation representations of fuzzy logic systems are introduced and several important conclusions are given. Then three important kinds of neural networks are defined, i.e. linear neural networks, rectangle wave neural networks and nonlinear neural networks. Then it is proved that nonlinear neural networks can be represented by rectangle wave neural networks. Based on the results mentioned above, the equivalence between fuzzy logic systems and feedforward neural networks is proved, which will be very useful for theoretical research or applications on fuzzy logic systems or neural networks by means of combining fuzzy logic systems with neural networks.
引用
收藏
页码:42 / 54
页数:13
相关论文
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