Auxiliary model method for transfer function estimation from noisy input and output data

DOI10.1016/j.apm.2014.12.040zbMath1443.93132OpenAlexW2038846853MaRDI QIDQ2282891

Yong Zhang, Zhe Zhao, Guimei Cui

Publication date: 20 December 2019

Published in: Applied Mathematical Modelling (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.apm.2014.12.040

zbMATH Keywords

least squaresparameter estimatesauxiliary modelerrors in variables systems

Mathematics Subject Classification ID

Estimation and detection in stochastic control theory (93E10) Least squares and related methods for stochastic control systems (93E24)

Related Items (4)

Auxiliary model based multi-innovation stochastic gradient identification algorithm for periodically non-uniformly sampled-data Hammerstein systems ⋮ Coupled least squares identification algorithms for multivariate output-error systems ⋮ A novel two-stage estimation algorithm for nonlinear Hammerstein-Wiener systems from noisy input and output data ⋮ Prescribed performance of discrete-time controller based on the dynamic equivalent data model

Cites Work

• Unnamed Item
• Hierarchical multi-innovation stochastic gradient algorithm for Hammerstein nonlinear system modeling
• An efficient hierarchical identification method for general dual-rate sampled-data systems
• Bias compensation methods for stochastic systems with colored noise
• Combined state and least squares parameter estimation algorithms for dynamic systems
• Identifiability of errors in variables dynamic systems
• Identification of errors-in-variables systems with nonlinear output observations
• Accuracy analysis of bias-eliminating least squares estimates for errors-in-variables systems
• Transfer function estimation from noisy input and output data
• Unbiased Recursive Least-Squares Estimation Utilizing Dichotomous Coordinate-Descent Iterations
• Parameter estimation of stochastic linear systems with noisy input
• A bias correction method for identification of linear dynamic errors-in-variables models
• Errors-in-variables methods in system identification

This page was built for publication: Auxiliary model method for transfer function estimation from noisy input and output data