Unifying some higher-order statistic-based methods for errors-in-variables model identification

DOI10.1016/j.automatica.2009.04.019zbMath1185.93140OpenAlexW1991889715MaRDI QIDQ963795

Wei Xing Zheng, Marion Gilson, Stéphane Thil, Hugues Garnier

Publication date: 14 April 2010

Published in: Automatica (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.automatica.2009.04.019

zbMATH Keywords

instrumental variablesystem identificationhigher-order statisticserrors-in-variables

Mathematics Subject Classification ID

Discrete-time control/observation systems (93C55) Identification in stochastic control theory (93E12)

Related Items (2)

Identification of EIV models by compensated PEM ⋮ Identification of EIV models with coloured input–output noise: combining PEM and covariance matching method

Cites Work

• Unnamed Item
• Maximum likelihood identification of noisy input-output models
• Frequency domain maximum likelihood estimation of linear dynamic errors-in-variables models
• Identification of stochastic linear systems in presence of input noise
• A higher-order correlation method for model-order and parameter estimation
• Third-order cumulants based methods for continuous-time errors-in-variables model identification
• Identification of continuous-time errors-in-variables models
• Accuracy analysis of bias-eliminating least squares estimates for errors-in-variables systems
• An improved bias-compensation approach for errors-in-variables model identification
• Identification of linear systems using input-output cumulants
• Extending the Frisch scheme for errors-in-variables identification to correlated output noise
• Identification of linear systems with noisy input using input-output cumulants
• Errors-in-variables methods in system identification

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