System identification: theory for the user
System identification: theory for the user
Subspace algorithms for the stochastic identification problem
Automatica (Journal of IFAC)
Automatica (Journal of IFAC) - Special issue on statistical signal processing and control
N4SID: subspace algorithms for the identification of combined deterministic-stochastic systems
Automatica (Journal of IFAC) - Special issue on statistical signal processing and control
Subspace-based methods for the identification of linear time-invariant systems
Automatica (Journal of IFAC) - Special issue on trends in system identification
Automatica (Journal of IFAC)
A linear regression approach to state-space subspace system identification
Signal Processing - Special issue: subspace methods, part II: system identification
Stochastic realization with exogenous inputs and “subspace-methods” identification
Signal Processing - Special issue: subspace methods, part II: system identification
Statistical analysis of novel subspace identification methods
Signal Processing - Special issue: subspace methods, part II: system identification
Experimental evidence showing that stochastic subspace identification methods may fail
Systems & Control Letters
Brief paper: An approach to closed-loop subspace identification by orthogonal decomposition
Automatica (Journal of IFAC)
Subspace-based system identification: weighting and pre-filtering of instruments
Automatica (Journal of IFAC)
Brief Subspace identification of closed loop systems by the orthogonal decomposition method
Automatica (Journal of IFAC)
Brief A stochastic realization algorithm via block LQ decomposition in Hilbert space
Automatica (Journal of IFAC)
On the ill-conditioning of subspace identification with inputs
Automatica (Journal of IFAC)
Hi-index | 22.15 |
A stochastic realization theory for a discrete-time stationary process with an exogenous input is developed by extending the classical CCA technique. Some stochastic subspace identification methods are derived by adapting the realization procedure to finite input-output data.