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title:
 
Methodology for adapting the parameters of a fuzzy system using the extended Kalman filter
publication:
 
EUSFLAT
part of series:
  Advances in Intelligent Systems Research
pages:   686 - 690
DOI:
  To be assigned soon (how to use a DOI)
author(s):
 
A. Javier, Jos¨¦ M., Mariano J., Agust¨ªn Jim¨¦nez, Basil M.
publication date:
 
July 2011
keywords:
 
Kalman filter, estimation, fuzzy system, modeling.
abstract:
 
When we try to analyze and to control a system whose model was obtained only based on input/output data, accuracy is essential in the model. On the other hand, to make the procedure practical, the modeling stage must be computationally efficient. In this regard, this paper presents the application of extended Kalman filter for the parametric adaptation of a fuzzy model.
copyright:
 
© Atlantis Press. This article is distributed under the terms of the Creative Commons Attribution License, which permits non-commercial use, distribution and reproduction in any medium, provided the original work is properly cited.
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