Strongly consistent coefficient estimate for errors-in-variables models

DOI10.1016/j.automatica.2004.12.007zbMath1091.93041OpenAlexW2044115643MaRDI QIDQ814009

Jun-Mei Yang, Chen, Hanfu

Publication date: 2 February 2006

Published in: Automatica (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.automatica.2004.12.007

zbMATH Keywords

convergence rateerrors-in-variablesstrong consistencyidentifiabilityARMA

Mathematics Subject Classification ID

Point estimation (62F10) Identification in stochastic control theory (93E12)

Related Items (9)

Overlapping decentralized approach to automation generation control of multi-area power systems ⋮ Recursive identification for dynamic linear systems from noisy input-output measurements ⋮ Output regulation for a class of uncertain nonlinear systems with nonlinear exosystems and its application ⋮ Recursive identification for multivariate errors-in-variables systems ⋮ Identification of errors-in-variables systems with ARMA observation noises ⋮ Adaptive rejection of non-linear disturbances in extended non-linear output feedback systems ⋮ Algorithms for recursive/semi-recursive bias-compensating least squares system identification within the errors-in-variables framework ⋮ Semi-global robust output regulation of minimum-phase nonlinear systems based on high-gain nonlinear internal model ⋮ On the identifiability of errors-in-variables models with white measurement errors

Cites Work

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• Parameter estimation for ARMA processes with errors in models
• On the uniqueness of prediction error models for systems with noisy input-output data
• IDENTIFIABILITY IN DYNAMIC ERRORS-IN-VARIABLES MODELS
• Least-squares identification for ARMAX models without the positive real condition
• Stochastic system identification with noisy input using cumulant statistics
• A Structure Theory for Linear Dynamic Errors-in-Variables Models
• Time delay estimation in unknown Gaussian spatially correlated noise

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