DocumentCode
3452156
Title
Identification of nonlinear systems by fuzzy models
Author
Yager, Ronald R. ; Filev, Dimitar P.
Author_Institution
Machine Intelligence Inst., Iona Coll., New Rochelle, NY, USA
fYear
1992
fDate
8-12 Mar 1992
Firstpage
1401
Lastpage
1408
Abstract
The concept of sampled probability distributions is introduced. A new formulation of the unified identification problem of quasi-linear fuzzy models (QLFMs) and quasi-nonlinear fuzzy models (D. Filev, 1990, 1991) that considers simultaneously the structure and parameter identification is proposed. A learning algorithm realizing structure and parameter identification of QLFMs is proposed
Keywords
fuzzy set theory; identification; nonlinear systems; probability; fuzzy set theory; learning algorithm; nonlinear systems; parameter identification; quasilinear fuzzy models; sampled probability distributions; structure identification; Classification algorithms; Educational institutions; Fuzzy control; Fuzzy reasoning; Fuzzy sets; Fuzzy systems; Input variables; Machine intelligence; Nonlinear systems; Parameter estimation; Probability distribution;
fLanguage
English
Publisher
ieee
Conference_Titel
Fuzzy Systems, 1992., IEEE International Conference on
Conference_Location
San Diego, CA
Print_ISBN
0-7803-0236-2
Type
conf
DOI
10.1109/FUZZY.1992.258710
Filename
258710
Link To Document