A new approach to fuzzy wavelet system modeling

Küçük Resim Yok

Tarih

2005

Dergi Başlığı

Dergi ISSN

Cilt Başlığı

Yayıncı

Elsevier Science Inc

Erişim Hakkı

info:eu-repo/semantics/openAccess

Özet

In this paper, we propose simple but effective two different fuzzy wavelet networks (FWNs) for system identification. The FWNs combine the traditional Takagi-Sugeno-Kang (TSK) fuzzy model and discrete wavelet transforms (DWT). The proposed FWNs consist of a set of if-then rules and, then parts are series expansion in terms of wavelets functions. In the first system, while the only one scale parameter is changing with it corresponding rule number, translation parameter sets are fixed in each rule. As for the second system, DWT is used completely by using wavelet frames. The performance of proposed fuzzy models is illustrated by examples and compared with previously published examples. Simulation results indicate the remarkable capabilities of the proposed methods. It is worth noting that the second FWN achieves high function approximation accuracy and fast convergence. (c) 2005 Elsevier Inc. All rights reserved.

Açıklama

Anahtar Kelimeler

fuzzy wavelet, fuzzy system models, learning, wavelet transform

Kaynak

International Journal of Approximate Reasoning

WoS Q Değeri

Q2

Scopus Q Değeri

Q1

Cilt

40

Sayı

3

Künye