Hammerstein system identification by non-parametric regression estimation

DOI10.1080/00207178708933731zbMath0613.93062OpenAlexW2028739315WikidataQ118592632 ScholiaQ118592632MaRDI QIDQ4721945

Włodzimierz Greblicki, Mirosław Pawlak

Publication date: 1987

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

Full work available at URL: https://doi.org/10.1080/00207178708933731

zbMATH Keywords

algorithmdiscrete-time, multiple-input nonlinear Hammerstein systemnon-parametric kernel estimate

Mathematics Subject Classification ID

Related Items (11)

Non-parametric identification of dynamic non-linear systems by a Hermite Series Approach ⋮ Identificaction of nonlinear block-oriented systems by the recursive kernel estimate ⋮ Unnamed Item ⋮ Identification of non-linear characteristics of a class of block-oriented non-linear systems via Daubechies wavelet-based models ⋮ Nonparametric estimation of nonlinear dynamic systems using semirecursive regression estimates ⋮ Wiener and Hammerstein uncertain models identification ⋮ Identification of nonlinear systems using a piecewise-linear hammerstein model ⋮ Global identification of nonlinear Hammerstein systems by recursive kernel approach ⋮ Controller design oriented model identification method for Hammerstein system ⋮ Recursive nonparametric identification of Hammerstein systems ⋮ Neural network approach for identification of Hammerstein systems

Cites Work

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