H. Alduwaish et al., HAMMERSTEIN MODEL IDENTIFICATION BY MULTILAYER FEEDFORWARD NEURAL NETWORKS, International Journal of Systems Science, 28(1), 1997, pp. 49-54
Citations number
21
Categorie Soggetti
System Science","Computer Science Theory & Methods","Operatione Research & Management Science
A new method for the identification of the nonlinear Hammer stein mode
l, consisting of a static linearity in cascade with a linear dynamic p
art, is introduced. The static nonlinearity is modelled by a multilaye
r feed forward neural network (MFNN) and the linear part is modelled b
y an autoregressive moving average (ARMA) model. A recursive algorithm
is developed to update the weights of the MFNN and the parameters of
the ARMA. The new method makes use of the well-known nonlinear mapping
ability of MFNN and avoids the restrictive assumptions of the previou
s identification methods. Two numerical examples are presented to illu
strate the performance of the developed model and recursive algorithm.