Identification of nonlinear errors-in-variables models.

DOI10.1016/j.automatica.2003.06.001zbMath1041.93020OpenAlexW2050366394MaRDI QIDQ1421445

István Vajk, Jenő Hetthéssy

Publication date: 26 January 2004

Published in: Automatica (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.automatica.2003.06.001

zbMATH Keywords

nonlinear system identificationerrors-in-variables modeleigenvalue-eigenvector decomposition

Mathematics Subject Classification ID

System identification (93B30) Nonlinear systems in control theory (93C10) Eigenvalue problems (93B60)

Related Items (9)

Adjusted least squares fitting of algebraic hypersurfaces ⋮ Nonlinearly Structured Low-Rank Approximation ⋮ Parameter estimation from noisy measurements ⋮ Recursive identification of errors-in-variables Wiener-Hammerstein systems ⋮ Robust fitting of ellipsoids by separating interior and exterior points during optimization ⋮ A bias-corrected estimator for nonlinear systems with output-error type model structures ⋮ Frisch scheme identification for dynamic diagonal bilinear models ⋮ Extended least-correlation estimates for errors-in-variables non-linear models ⋮ Identification of EIV models with coloured input–output noise: combining PEM and covariance matching method

Cites Work

• Estimation for the nonlinear functional relationship
• Consistency of system identification by global total least squares
• Subspace algorithms for the identification of multivariable dynamic errors-in-variables models
• Identification of dynamic errors-in-variables models
• Identification of linear systems with input and output noise: the Koopmans-Levin method
• Unnamed Item

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