Fuzzy logic systems are equivalent to feedforward neural networks

被引:0
作者
李洪兴
机构
[1] DepartmentofMathematics,BeijingNormalUniversity,Beijing,China
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
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
<正> 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
共 2 条
[1]  
Interpolation mechanism of fuzzy control[J]. 李洪兴.Science in China(Series E:Technological Sciences). 1998(03)
[2]   典型模糊控制器的结构分析 [J].
张乃尧 .
模糊系统与数学, 1997, (02) :12-23