Robust parametric identification procedure of stochastic nonlinear continuous-discrete systems

Based on the weighted maximum likelihood method and the correntropy cubature Kalman filter, software to solve the problem of parametric estimation of models of stochastic nonlinear continuous-discrete systems in the presence of anomalous observations in the measurement data is developed. The effectiveness of the proposed procedure is demonstrated on two model structures for the stochastic and the grouped ordering of anomalous data.