ON THE FUNCTIONAL EQUIVALENCE OF FUZZY INFERENCE SYSTEMS AND SPLINE-BASED NETWORKS

被引：17

作者：

HUNT, KJ

HAAS, R

BROWN, M

机构：

[1] DAIMLER BENZ AG,SYST TECHNOL RES,D-10559 BERLIN,GERMANY

[2] UNIV SOUTHAMPTON,DEPT ELECTR & COMP SCI,IMAGE SPEECH & INTELLIGENT SYST RES GRP,SOUTHAMPTON SO9 5NH,HANTS,ENGLAND

来源：

INTERNATIONAL JOURNAL OF NEURAL SYSTEMS | 1995年 / 6卷 / 02期

关键词：

D O I：

10.1142/S0129065795000135

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

The conditions under which spline-based networks are functionally equivalent to the Takagi-Sugeno-model of fuzzy inference are formally established. We consider a generalized form of basis function network whose basis functions are splines. The result admits a wide range of fuzzy membership functions which are commonly encountered in fuzzy systems design. We use the theoretical background of functional equivalence to develop a hybrid fuzzy-spline net for inverse dynamic modeling of a hydraulically driven robot manipulator.

引用

页码：171 / 184

页数：14

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