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 :
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