Approximation of fuzzy functions by regular fuzzy neural networks

Authors:
Huan Huang;Congxin Wu
Affiliations:
Department of Mathematics, Jimei University, Xiamen 361021, China;Department of Mathematics, Harbin Institute of Technology, Harbin 150001, China
Venue:
Fuzzy Sets and Systems
Year:
2011

Citing 10
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Abstract

In this paper, we investigate the ability of regular fuzzy neural networks to provide approximations to fuzzy functions. Since the operation of regular fuzzy neural networks is based on Zadeh's extension principle, we first present a level characterization of the Zadeh's extensions of level-continuous fuzzy-valued functions and consider the continuity of these extensions. On the basis of this, we give characterizations of fuzzy functions which can be approximated by a class of four-layer regular fuzzy neural networks according to supremum-metric and level convergence.