Complex-valued adaptive neuro fuzzy inference system-CANFIS

被引：0
|
作者：
Malekzadeh, A [1 ]
Akbarzadeh, MR [1 ]
机构：
[1] Ferdowsi Univ, Dept Elect Engn, Mashhad, Iran
来源：
Soft Computing with Industrial Applications, Vol 17 | 2004年 / 17卷
关键词：
complex fuzzy sets; fuzzy logic; complex implication function and inference system (CFIS); complex-valued neural network; Stone-Weierstrass theorem;
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：
This paper reports oil a novel framework for Complex-valued Adaptive Neuro Fuzzy lnference System. A hybrid of ANFIS and Complex Fuzzy Sets, the CANFIS promises to enjoy the strong features of its predecessors in complex domain. The proposed framework could have utility in distributed and time-delayed systems. The universal approximation property of CANFIS for complex domain of functions is also proved. Finally, CANFIS is used here to approximate a simple complex function.
引用
收藏
页码：477 / 482
页数：6
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