Title :
Instrumental variable based maximum likelihood evolving fuzzy algorithm for nonlinear system identification
Author :
Orlando Donato Rocha Filho;Ginalber Luiz de Oliveira Serra
Author_Institution :
Federal Institute of Education, Science and Technology, Sã
fDate :
6/1/2015 12:00:00 AM
Abstract :
This paper presents an overview of a specific application fo computational intelligence techniques, specifically, evolving fuzzy systems: online fuzzy inference system with Takagi-Sugeno evolving structure, which employs an adaptive distance norm based on the maximum likelihood criterion online with instrumental variable recursive parameter estimation. The performance and application of the proposed methodology is based on the black box modeling.
Keywords :
"Clustering algorithms","Instruments","Covariance matrices","Maximum likelihood estimation","Prototypes","Partitioning algorithms"
Conference_Titel :
Industrial Electronics (ISIE), 2015 IEEE 24th International Symposium on
Electronic_ISBN :
2163-5145
DOI :
10.1109/ISIE.2015.7281448
