Identification of continuous-time systems using arbitrary signals
Automatica (Journal of IFAC)
Automatica (Journal of IFAC)
Identification of Continuous-Time Systems: Methodology and Computer Implementation
Identification of Continuous-Time Systems: Methodology and Computer Implementation
Continuous-time identification of SISO systems using Laguerre functions
IEEE Transactions on Signal Processing
Identification of continuous-time models
IEEE Transactions on Signal Processing
Stochastic theory of continuous-time state-space identification
IEEE Transactions on Signal Processing
Time series analysis in the frequency domain
IEEE Transactions on Signal Processing
Convergence properties of the generalised least squares identitication method
Automatica (Journal of IFAC)
IEEE Transactions on Information Theory
Frequency-domain identification of continuous-time ARMA models from sampled data
Automatica (Journal of IFAC)
Hi-index | 22.15 |
This paper treats the identification of continuous-time models using arbitrary band-limited excitation signals. A modeling approach is presented that has the following two advantages: (1)asymptotically (the amount of data tends to infinity) there is no approximation error over the complete frequency band from DC to Nyquist, (2)it allows to identify general parametric noise models. The key idea is to combine a continuous-time plant model with a discrete-time noise model (=hybrid Box-Jenkins model structure).