Optimal experiment designs with respect to the intended model application
Automatica (Journal of IFAC)
The statistical theory of linear systems
The statistical theory of linear systems
The information matrix of multiple-input single-output time series models
Journal of Computational and Applied Mathematics
The Cramér-Rao lower bound for noisy input-output systems
Signal Processing
Survey paper: Errors-in-variables methods in system identification
Automatica (Journal of IFAC)
Identifiability of errors in variables dynamic systems
Automatica (Journal of IFAC)
On the equivalence of time and frequency domain maximum likelihood estimation
Automatica (Journal of IFAC)
Brief paper: Asymptotic statistical analysis for model-based control design strategies
Automatica (Journal of IFAC)
Paper: Unprejudiced optimal open loop input design for identification of transfer functions
Automatica (Journal of IFAC)
Guaranteed non-asymptotic confidence regions in system identification
Automatica (Journal of IFAC)
Least-squares estimation of a class of frequency functions: A finite sample variance expression
Automatica (Journal of IFAC)
On the frequency domain accuracy of closed-loop estimates
Automatica (Journal of IFAC)
Hi-index | 22.14 |
In this paper, we study the accuracy of linear multiple-input multiple-output (MIMO) models obtained by maximum likelihood estimation. We present a frequency-domain representation for the information matrix for general linear MIMO models. We show that the variance of estimated parametric models for linear MIMO systems satisfies a fundamental integral trade-off. This trade-off is expressed as a multivariable 'water-bed' effect. An extension to spectral estimation is also discussed.