Universal approximations of continuous fuzzy-valued functions by multi-layer regular fuzzy neural networks

被引：35

作者：

Liu, PY ^{[1
]}

机构：

[1] Natl Univ Def Technol, Dept Syst Engn & Math, Changsha 410073, Hunan, Peoples R China

来源：

FUZZY SETS AND SYSTEMS | 2001年 / 119卷 / 02期

关键词：

regular fuzzy neural networks; fuzzy-valued polynomials; universal approximations; universal approximator;

D O I：

10.1016/S0165-0114(99)00132-3

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

The fact that four-layer feedforward regular fuzzy neural networks with sigmoid function in the first hidden layer are capable of approximately representing continuous fuzzy valued functions on any compact set of R is shown. At first, Bernstein polynomials associated with fuzzy valued functions are employed to approximate continuous fuzzy valued function defined on a compact set. Secondly, by the conclusions related to standard feedforward networks, universal approximations of continuous fuzzy valued functions by regular fuzzy neural networks are obtained. (C) 2001 Elsevier Science B.V. All rights reserved.

引用

页码：313 / 320

页数：8

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