Title :
MIMO evolving learning based on maximum likelihood algorithm applied to black box fuzzy modeling for systems identification design
Author :
Orlando Donato Rocha Filho;Ginalber Luiz de Oliveira Serra
Author_Institution :
Department of Electroelectronics, Laboratory of Computational Intelligence Applied to Techonology, Federal Institute of Education, Science and Technology, Sã
fDate :
7/1/2015 12:00:00 AM
Abstract :
This paper presents an overview of a specific application to 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","Prototypes","Maximum likelihood estimation","Partitioning algorithms","Algorithm design and analysis"
Conference_Titel :
Informatics in Control, Automation and Robotics (ICINCO), 2015 12th International Conference on
