Fuzzy inference systems with no any rule base and linearly parameter growth

被引：3
|
作者：
Shitong Wang
Korris F. L. Chung
Jieping Lu
Bin Han
Dewen Hu
机构：
[1] Southern Yangtee University,Department of Computer, School of Information
[2] HongKong Polytechnic University,Department of Computing
[3] Southeast University,Department of Computer
[4] EastChina Shipbuilding Institute,Department of Computer
[5] National Defense University of Science & Technology,School of Automation
来源：
Journal of Control Theory and Applications | 2004年 / 2卷 / 2期
关键词：
Fuzzy inference; Fuzzy systems; Universal approximation; Computational complexity; Linearly parameter growth;
D O I：
10.1007/s11768-004-0067-x
中图分类号：
学科分类号：
摘要：
A class of new fuzzy inference systems New-FISs is presented. Compared with the standard fiazzy system, New-FIS is still a universal approximator and has no fiizzy rule base and linearly parameter growth. Thus, it effectively overcomes the second “curse of dimensionality”: there is an exponential growth in the number of parameters of a fuzzy system as the number of input variables, resulting in surprisingly reduced computational complexity and being especially suitable for applications, where the complexity is of the first importance with respect to the approximation accuracy.
引用
收藏
页码：185 / 192
页数：7
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