Stochastic Theory of Continuous-Time State-Space Identification
Presents theory, algorithms and validation results for system identification of continuous-time state-space models from finite input-output sample sequences. The algorithms developed are methods of subspace model identification and stochastic realization adapted to the continuous-time context. The resulting model can be decomposed into an input-output model and a stochastic innovations model. Usin