Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/50537
Title: Building fuzzy graphs from samples of nonlinear functions
Authors: Tan, S. 
Yu, Y.
Wang, P.-Z. 
Keywords: Function sampling
Fuzzy graphs
Nonlinear functions
Recursive learning
Universal approximation
Issue Date: 1998
Source: Tan, S.,Yu, Y.,Wang, P.-Z. (1998). Building fuzzy graphs from samples of nonlinear functions. Fuzzy Sets and Systems 93 (3) : 337-352. ScholarBank@NUS Repository.
Abstract: This paper considers the problem of constructing fuzzy graphs from samples of multi-dimensional nonlinear functions to meet a precision requirement. It starts by defining the basic notions of fuzzy granulation, fuzzy graph, fuzzification and defuzzification. The formulation of the problem is then stated in a fuzzy granulation and function approximation framework. This is followed by the development of a recursive scheme that builds a fuzzy graph by generating a set of fuzzy rules and membership functions from the samples of a nonlinear function. Rigorous analysis is carried out to establish the convergence of such a recursive scheme. A few illustrative examples are also used to assess both the efficacy and the efficiency of the proposed scheme. © 1998 Elsevier Science B.V.
Source Title: Fuzzy Sets and Systems
URI: http://scholarbank.nus.edu.sg/handle/10635/50537
ISSN: 01650114
Appears in Collections:Staff Publications

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