On the uniqueness of prediction error models for systems with noisy input-output data

DOI10.1016/0005-1098(87)90083-5zbMath0616.93074OpenAlexW1966915892MaRDI QIDQ1821753

Petre Stoica, Arye Nehorai

Publication date: 1987

Published in: Automatica (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/0005-1098(87)90083-5

zbMATH Keywords

system identificationprediction errorglobal identifiabilityparameter estimatesnoisy systems

Mathematics Subject Classification ID

Inference from stochastic processes and prediction (62M20) Discrete-time control/observation systems (93C55) Linear systems in control theory (93C05) Identification in stochastic control theory (93E12)

Related Items (9)

Consistent identification of stochastic linear systems with noisy input- output data ⋮ Recursive identification for multivariate errors-in-variables systems ⋮ A predictive demand model for systems planning, using noisy realization theory ⋮ Identification of errors-in-variables systems with ARMA observation noises ⋮ Identifiability of errors in variables dynamic systems ⋮ Unnamed Item ⋮ On the identifiability of errors-in-variables models with white measurement errors ⋮ Errors-in-variables methods in system identification ⋮ Strongly consistent coefficient estimate for errors-in-variables models

Cites Work

• Unnamed Item
• Unnamed Item
• Identification of scalar errors-in-variables models with dynamics
• Identification of stochastic linear systems in presence of input noise
• Introduction to stochastic control theory
• IDENTIFIABILITY IN DYNAMIC ERRORS-IN-VARIABLES MODELS

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