Estimation of an N-L-N Hammerstein-Wiener model (Q1614436)
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scientific article; zbMATH DE number 1797143
| Language | Label | Description | Also known as |
|---|---|---|---|
| English | Estimation of an N-L-N Hammerstein-Wiener model |
scientific article; zbMATH DE number 1797143 |
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Estimation of an N-L-N Hammerstein-Wiener model (English)
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5 September 2002
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Parametric identification of a noisy nonlinear SISO Hammerstein-Wiener dynamical model is considered. A relaxation recursive identification scheme to determine approximate model parameters is proposed. The nonlinear static characteristics are parameterized by using cubic splines, and the linear dynamics is represented by a high-order ARX model. This yields the identification error bilinear-in-parameters. The convergence of the scheme to the best model parameters is examined. Simulation examples illustrate the effectiveness of the method.
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identification
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nonlinear process
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block-oriented model
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parameter estimation
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relaxation algorithm
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Hammerstein-Wiener dynamical model
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cubic splines
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