NDLI: Nonlinear system identification of a lower limb model by Fuzzy Wavelet Neural Networks

Content Provider	IEEE Xplore Digital Library
Author	Linhares, L.L.S. Medeiros de Araujo, J. Meneghetti U. Araujo, F.
Copyright Year	2013
Description	Author affiliation: Dept. of Comput. Eng. & Autom., Fed. Univ. of Rio Grande do Norte, Natal, Brazil (Linhares, L.L.S.; Medeiros de Araujo, J.; Meneghetti U. Araujo, F.)
Abstract	This paper presents the identification of a simulated nonlinear system that represents the dynamical mechanism of the human lower limb. The study and application of this model may have a relevant importance in the research area of rehabilitation of patients suffering from any kind of paralysis of their lower limbs. Here, a Fuzzy Wavelet Neural Network (FWNN) is used to identify the lower limb model under study. In order to evaluate the FWNN model, it was validated in two distinct situations. Firstly it was considered that the original model does not suffer any modification in its parameters and, in the second case, the viscous coefficient was reduced. In this way, it was possible to analyze the FWNN model robustness in terms of this parameter change. The performance of the FWNN was also compared with other two neural network structures: Multilayer Perceptron (MLP) and Wavelet Neural Network (WNN).
Sponsorship	IEEE Ind. Electron. Soc.
Starting Page	3628
Ending Page	3633
File Size	335458
Page Count	6
File Format	PDF
ISBN	9781479902248
ISSN	1553572X
DOI	10.1109/IECON.2013.6699712
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-11-10
Publisher Place	Austria
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Object oriented modeling Mathematical model Biological neural networks Vectors Analytical models Neurons
Content Type	Text
Resource Type	Article

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