Fuzzy rule-base driven orthogonal approximation
Küçük Resim Yok
Tarih
2008
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
In this study, orthogonal approximation concept is applied to fuzzy systems. We propose a new useful model adapted from the well-known Sugeno type fuzzy system. The proposed fuzzy model is a generalization of the zero-order Sugeno fuzzy system model. Instead of linear functions in standard Sugeno model, we use nonlinear functions in the consequent part. The nonlinear functions are selected from a trigonometric orthogonal basis. Orthogonal function parameters are trained along with the Sugeno fuzzy system. The proposed model is demonstrated using three simulations-a nonlinear piecewise-continuous scalar function modeling and filtering, nonlinear dynamic system identification, and time series prediction. Finally some performance comparisons are carried out. © 2007 Springer-Verlag London Limited.
Açıklama
Anahtar Kelimeler
Fuzzy system modeling, Orthogonal functions, Time series prediction
Kaynak
Neural Computing and Applications
WoS Q Değeri
Scopus Q Değeri
Q1
Cilt
17
Sayı
05.Jun
