By Topic

Identification of Quadratic Non Linear Systems Using Higher Order Statistics and Fuzzy Models

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

5 Author(s)
Antari, J. ; Dept. of Phys., Semlalia Cadi Ayyad Univ. ; Iqdour, R. ; Safi, S. ; Zeroual, A.
more authors

In this work we compare tow methods for the identification of non-linear systems. The first one uses a quadratic non linear model of which parameters are estimated using a new algorithm based on the fourth order cumulants. The second one is based on the Takagi-Sugeno fuzzy models. The simulation results show that the fuzzy models give the good results in noiseless and weak noise environment. However the quadratic model of which parameters are identified using the proposed algorithm works well in the high noise environment case

Published in:

Acoustics, Speech and Signal Processing, 2006. ICASSP 2006 Proceedings. 2006 IEEE International Conference on  (Volume:3 )

Date of Conference:

14-19 May 2006