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A joint frequency-position domain structure identification of nonlinear discrete-time systems by neural networks

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3 Author(s)
Elramsisi, A.M. ; Sch. of Eng. & Comput. Sci., Oakland Univ., Rochester, MI, USA ; Zohdy, M.A. ; Loh, N.K.

A new technique is proposed to identify the structure and the parameters of nonlinear discrete-time system models. The structure is represented in a frequency-position domain of Gabor basis functions (GBFs). A simplification to the GBF is also presented, where the spatial Gaussian envelope of GBF is replaced with a triangular one. A modification to the GBF has also been introduced in order to suppress the effects of noise on the procedure. A three-layered neural network, augmented with nonuniform sampling, is described for solving the system identification problem

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Automatic Control, IEEE Transactions on  (Volume:36 ,  Issue: 5 )