The standard continuous time state space model with stochastic disturbances contains the mathematical abstraction of continuous time white noise. To work with well defined, discrete time observations, it is necessary to sample the model with care. The basic issues are well known, and have been discussed in the literature. However, the consequences have not quite penetrated the practice of estimation and identification. One example is that the standard model of an observation, being a snapshot of the current state plus noise independent of the state, cannot be reconciled with this picture. Another is that estimation and identification of time continuous models require a more careful treatment of the sampling formulas. We discuss and illustra...
Identification of time-continuous models from sampled data is a long standing topic of discussion, a...
Identification of time-continuous models from sampled data is a long standing topic of discussion, a...
The problem of estimating continuous--time stochastic models from discrete-- time data is addressed....
The standard continuous time state space model with stochastic disturbances contains the mathematica...
This paper presents theory, algorithms and validation results for system identification of continuou...
This contribution reviews theory, algorithms, and validation results for system identification of co...
This paper presents theory, algorithms and validation results for system identification of continuou...
This contribution reviews theory, algorithms, and validation results for system identification of co...
We consider a multivariate continuous-time process, generated by a system of linear stochastic diffe...
We consider a multivariate continuous-time process, generated by a system of linear stochastic diffe...
We consider a multivariate continuous-time process, generated by a system of linear stochastic diffe...
This lecture surveys the recent literature on estimating continuous-time models using discrete obser...
This contribution reviews theory, algorithms, and validation results for system identification of co...
Identification of time-continuous models from sampled data is a long standing topic of discussion, a...
We consider a multivariate continuous time process, generated by a system of linear stochastic diffe...
Identification of time-continuous models from sampled data is a long standing topic of discussion, a...
Identification of time-continuous models from sampled data is a long standing topic of discussion, a...
The problem of estimating continuous--time stochastic models from discrete-- time data is addressed....
The standard continuous time state space model with stochastic disturbances contains the mathematica...
This paper presents theory, algorithms and validation results for system identification of continuou...
This contribution reviews theory, algorithms, and validation results for system identification of co...
This paper presents theory, algorithms and validation results for system identification of continuou...
This contribution reviews theory, algorithms, and validation results for system identification of co...
We consider a multivariate continuous-time process, generated by a system of linear stochastic diffe...
We consider a multivariate continuous-time process, generated by a system of linear stochastic diffe...
We consider a multivariate continuous-time process, generated by a system of linear stochastic diffe...
This lecture surveys the recent literature on estimating continuous-time models using discrete obser...
This contribution reviews theory, algorithms, and validation results for system identification of co...
Identification of time-continuous models from sampled data is a long standing topic of discussion, a...
We consider a multivariate continuous time process, generated by a system of linear stochastic diffe...
Identification of time-continuous models from sampled data is a long standing topic of discussion, a...
Identification of time-continuous models from sampled data is a long standing topic of discussion, a...
The problem of estimating continuous--time stochastic models from discrete-- time data is addressed....