Estimation of quantized linear errors-in-variables models

DOI10.1016/0005-1098(95)00070-DzbMath0837.93072MaRDI QIDQ1902579

Vikram Krishnamurthy

Publication date: 12 May 1996

Published in: Automatica (Search for Journal in Brave)

zbMATH Keywords

Gaussian processtime series analysisestimation algorithmdynamic shock-error modelsbinary series estimation

Mathematics Subject Classification ID

Control/observation systems involving computers (process control, etc.) (93C83) Discrete-time control/observation systems (93C55) Identification in stochastic control theory (93E12)

Related Items (3)

Impulse response identification from input/output binary measurements ⋮ Fixed-order FIR approximation of linear systems from quantized input and output data ⋮ Identification of Wiener systems with binary-valued output observations

Cites Work

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• Maximum likelihood estimation of the dynamic shock-error model
• On covariance function tests used in system identification
• Linear dynamic errors-in-variables models. Some structure theory
• Autoregressive and window estimates of the inverse correlation function
• Some Graphical Considerations in Time Series Analysis
• On-line estimation of dynamic shock-error models based on the Kullback Leibler information measure
• Estimation of noisy quantized Gaussian AR time-series with randomly varying observation coefficient

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