Active parametric identification of stochastic continuous-discrete systems obtained by statistical linearization

For stochastic continuous-discrete models obtained by statistical linearization, we consider the theoretical and applied aspects of active parametric identification in the case where the parameters of mathematical models to be estimated occur in the state, control, and perturbation matrices and the covariance matrices of dynamic noise and measurement errors. The results are given. An example of optimal parameter estimation for one model structure is considered.