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

Author(s): Ayachi Errachdi | Ihsen Saad | Mohamed Benrejeb

Journal: Intelligent Control and Automation
ISSN 2153-0653

Volume: 02;
Issue: 03;
Start page: 167;
Date: 2011;
Original page

Keywords: Neural Networks | Multivariable System | Stochastic | Learning Rate | Modeling

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.
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