Extending the functional equivalence of radial basis function networks and fuzzy inference systems

被引：78

作者：

Hunt, KJ

Haas, R

MurraySmith, R

机构：

[1] Daimler-Benz AG

[2] Daimler-Benz AG Systems Technology Research

来源：

IEEE TRANSACTIONS ON NEURAL NETWORKS | 1996年 / 7卷 / 03期

关键词：

D O I：

10.1109/72.501735

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

We establish the functional equivalence of a generalized class of Gaussian radial basis function (RBF's) networks and the full Takagi-Sugeno model of fuzzy inference. This generalizes an existing result which applies to the standard Gaussian RBF network and a restricted form of the Takagi-Sugeno fuzzy system. The more general framework allows the removal of some of the restrictive conditions of the previous result.

引用

页码：776 / 781

页数：6

共 17 条

[1]

[Anonymous], 1979, ADV FUZZY SET THEORY

[2]

Broomhead D. S., 1988, Complex Systems, V2, P321

[3]

FOSS BA, 1993, P 3 INT C IND FUZZ C

[4]

HUNT KJ, 1995, INT J NEURAL SYS JUN

[5] FUNCTIONAL EQUIVALENCE BETWEEN RADIAL BASIS FUNCTION NETWORKS AND FUZZY INFERENCE SYSTEMS [J].

JANG, JSR ;

SUN, CT .

IEEE TRANSACTIONS ON NEURAL NETWORKS, 1993, 4 (01) :156-159

[6]

Johansen T. A., 1992, Proceedings of the 1992 American Control Conference (IEEE Cat. No.92CH3072-6), P3037

[7]

JOHANSEN TA, 1994, THESIS NORGES TH TRO

[8]

JONES RD, 1989, P IEEE C NEUR NETW

[9]

KOSKO B, 1992, NEURAL NETS FUZZY SY

[10] Fast Learning in Networks of Locally-Tuned Processing Units [J].

Moody, John ;

Darken, Christian J. .

NEURAL COMPUTATION, 1989, 1 (02) :281-294

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