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Neural Modeling of Multivariable Nonlinear Stochastic System. Variable Learning Rate Case

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DOI: 10.4236/ica.2011.23020    3,983 Downloads   6,749 Views   Citations
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Ayachi Errachdi, Ihsen Saad, Mohamed Benrejeb

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ABSTRACT

The objective of this paper is to develop a variable learning rate for neural modeling of multivariable nonlinear stochastic system. The corresponding parameter is obtained by gradient descent method optimization. The effectiveness of the suggested algorithm applied to the identification of behavior of two nonlinear stochastic systems is demonstrated by simulation experiments.

KEYWORDS

Neural Networks, Multivariable System, Stochastic, Learning Rate, Modeling

Cite this paper

A. Errachdi, I. Saad and M. Benrejeb, "Neural Modeling of Multivariable Nonlinear Stochastic System. Variable Learning Rate Case," Intelligent Control and Automation, Vol. 2 No. 3, 2011, pp. 167-175. doi: 10.4236/ica.2011.23020.

Conflicts of Interest

The authors declare no conflicts of interest.

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