Generalized Kernel Regression Estimate for the Identification of Hammerstein Systems

DOI10.2478/v10006-007-0018-zzbMath1119.93416OpenAlexW2112851454MaRDI QIDQ5308321

Grzegorz Mzyk

Publication date: 27 September 2007

Published in: International Journal of Applied Mathematics and Computer Science (Search for Journal in Brave)

Full work available at URL: https://eudml.org/doc/207831

zbMATH Keywords

kernel estimationnonparametric regressionHammerstein system

Mathematics Subject Classification ID

System identification (93B30) Nonlinear systems in control theory (93C10) Identification in stochastic control theory (93E12)

Related Items (7)

Hammerstein system identification by non-parametric instrumental variables ⋮ A nonparametric kernel-based approach to Hammerstein system identification ⋮ Nonparametric instrumental variables for identification of block-oriented systems ⋮ On-line wavelet estimation of Hammerstein system nonlinearity ⋮ Regression function and noise variance tracking methods for data streams with concept drift ⋮ On-line parameter and delay estimation of continuous-time dynamic systems ⋮ Semirecursive nonparametric algorithms for Hammerstein systems with stochastic autocorrelated input

Uses Software

• KernSmooth

Cites Work

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