Identification of non-minimum phase linear stochastic systems

Automatica

Volumn 22, Issue 4, 1986, Pages 457-464

  Tugnait, Jitendra K ^a  

^a EXXONMOBIL UPSTREAM RESEARCH COMPANY   (United States)

Author keywords

non minimum phase systems; Parameter estimation; stochastic systems; system identification

Indexed keywords

CONTROL SYSTEMS, LINEAR;

NON-GAUSSIAN WHITE NOISE; NON-MINIMUM PHASE SYSTEMS; PARAMETER ESTIMATION; TIME-INVARIANT SYSTEM;

CONTROL SYSTEMS, STOCHASTIC;

EID: 0022754016     PISSN: 00051098     EISSN: None     Source Type: Journal    
DOI: 10.1016/0005-1098(86)90050-6     Document Type: Article

References (26)

1. A new look at the statistical model identification
2. Model approximations via prediction error identification
3. Maximum likelihood and prediction error methods
4. Zeros of sampled systems
5. Uniqueness of the maximum likelihood estimates of the parameters of an ARMA model
6. Likelihood ratios, posterior odds, and information criteria
7. Robust identification of a nonminimum phase system Blind adjustment of linear equalizer in data communications
8. An introduction to polyspectra
9. Asymptotic theory of estimates of kth order spectra
10. Computation and interpretation of kth order spectra
11. On minimum entropy deconvolution
12. Computational aspects of maximum likelihood estimation and reduction in sensitivity function calculation
13. Spectral estimation fact or fiction
14. Inconsistency of the AIC rule for estimating the order of aritoregressive models
15. Identifiability of nonminimum phase linear stochastic systems
16. Deconvolution and estimation of transfer function phase and coefficients for non-Gaussian linear processes
17. Convergence analysis of parametric identification methods
18. Asymptotic behavior of the extended Kalman filter as a parameter estimator for linear systems
19. Adaptive controllers for discrete-time systems with arbitrary zeros: an overview
20. Absolute value optimization to estimate phase properties of stochastic time series
21. Spectral estimation for noisy signals observed through a linear system