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- W2615497364 abstract "This paper presents an off-line identification-based modelling method for a class of smooth SISO nonlinear systems for the purposes of process control, output prediction or dynamics reconstruction. A pseudo-linear ARX (RBF-ARX) model with system operating-point dependent Gaussian RBF network-type coefficients is built to characterize the system. The RBF-ARX model is off-line identified, and the structured nonlinear parameter optimization method (Peng, et al. 2002) is applied to estimate its parameters. Output stability of the estimated RBF-ARX model is investigated in dynamics reconstruction problem. Comparisons of the RBF-ARX model and the on-line estimated linear time-varying ARX model are illustrated in case study." @default.
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- W2615497364 date "2003-09-01" @default.
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- W2615497364 title "Nonlinear system modelling using the RBF neural network-based regressive model" @default.
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- W2615497364 doi "https://doi.org/10.1016/s1474-6670(17)34783-3" @default.
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