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http://dx.doi.org/10.5391/JKIIS.2002.12.5.397

The wavelet neural network using fuzzy concept for the nonlinear function learning approximation  

Byun, Oh-Sung (원광대학교 전기ㆍ전자 및 정보공학부)
Moon, Sung-Ryong (원광대학교 전기ㆍ전자 및 정보공학부)
Publication Information
Journal of the Korean Institute of Intelligent Systems / v.12, no.5, 2002 , pp. 397-404 More about this Journal
Abstract
In this paper, it is proposed wavelet neural network using the fuzzy concept with the fuzzy and the multi-resolution analysis(MRA) of wavelet transform. Also, it wishes to improve any nonlinear function learning approximation using this system. Here, the fuzzy concept is used the bell type fuzzy membership function. And the composition of wavelet has a unit size. It is used the backpropagation algorithm for learning of wavelet neural network using the fuzzy concept. It is used the multi-resolution analysis of wavelet transform, the bell type fuzzy membership function and the backpropagation algorithm for learning. This structure is confirmed to be improved approximation performance than the conventional algorithms from one dimension and two dimensions function through simulation.
Keywords
Wavelet neural network; Approximation; MRA; Fuzzy concept; Bell type; backpropagation;
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