Linear identification of ARMA processes

Automatica

Volumn 18, Issue 4, 1982, Pages 461-466

  Mayne, D Q ^a   Firoozan, F ^a  

^a IMPERIAL COLLEGE LONDON   (United Kingdom)

Author keywords

filtering; Identification; least squares approximations; nonlinear filtering; parameter estimation

Indexed keywords

CONTROL SYSTEMS;

EID: 0020155335     PISSN: 00051098     EISSN: None     Source Type: Journal    
DOI: 10.1016/0005-1098(82)90074-7     Document Type: Article

References (19)

1. Automatic construction of linear stochastic dynamic models for stationary industrial processes with random disturbances using operating records
2. Numerical identification of linear dynamic systems from normal operating records
3. Consistent autoregressive spectral estimates
4. Prediction error identification methods for stationary stochastic processes
5. Generalized least squares estimation of the parameters of a dynamic model
6. The fitting of time-series models
7. Linear parameter estimation methods for identifying dynamic systems
8. Parameter estimation in multivariate stochastic difference equations
9. Parameter estimation
10. Convergence of a finite autoregressive model of an ARMA system
11. Two stage least squares estimators and their recursive approximations
12. Consistency of maximum likelihood estimation for ARMA processes
13. Convergence properties of the generalised least squares identification method
14. Some notes on extensions of the least squares identification method
15. Ergodicity results for sample covariances
16. Analysis of a three stage identification method
17. Identification of linear discrete-time systems using the instrumental variable approach