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D. C. Psichogios and L. H. Ungar, “Direct and Indirect Model-Based Control Using Artificial Neural Networks,” Industrial and Engineering Chemistry Research, Vol. 30, No. 12, 1991, pp. 25-64. doi:10.1021/ie00060a009

has been cited by the following article:

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

  AUTHORS: Ayachi Errachdi, Ihsen Saad, Mohamed Benrejeb

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

  JOURNAL NAME: Intelligent Control and Automation, Vol.2 No.3, August 8, 2011

  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.