Hammerstein system identification through best linear approximation inversion and regularisation

DOI10.1080/00207179.2017.1329550zbMath1397.93211OpenAlexW2617044081MaRDI QIDQ5375894

Johan A. K. Suykens, Koen Tiels, Ricardo Castro-Garcia, Oscar Mauricio Agudelo

Publication date: 17 September 2018

Published in: International Journal of Control (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/00207179.2017.1329550

zbMATH Keywords

frequency domainHammerstein systemsnonlinear system identificationleast squares support vector machinesbest linear approximationlinear block inversion

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Nonlinear systems in control theory (93C10) Linear systems in control theory (93C05) Least squares and related methods for stochastic control systems (93E24) Identification in stochastic control theory (93E12)

Related Items (1)

Adaptive filtering scheme for parameter identification of nonlinear Wiener–Hammerstein systems and its application

Uses Software

• Wiener-Hammerstein Benchmark

Cites Work

• Convergence of the iterative algorithm for a general Hammerstein system identification
• Identification of nonlinear systems using neural networks and polynomial models. A block-oriented approach.
• Block-oriented nonlinear system identification
• An optimal two-stage identification algorithm for Hammerstein-Wiener nonlinear systems
• Identification of systems containing linear dynamic and static nonlinear elements
• Decoupling the linear and nonlinear parts in Hammerstein model identification
• Identification of MIMO Hammerstein models using least squares support vector machines
• Identification of non-linear stochastic systems by state dependent parameter estimation
• Identification of Hammerstein systems without explicit parameterisation of non-linearity
• Parametric and nonparametric identification of linear systems in the presence of nonlinear distortions-a frequency domain approach
• Frequency domain system identification with missing data
• Frequency domain identification of hammerstein models
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