This analysis addresses the identification problem for discrete systems with random and interval parameters, suggesting new methods for resolution.
The identification problem for a discrete object with random and interval parameters is considered. The random parameters in the model are set as Gaussian random sequences. To represent the interval parameters, a probabilistic approach is used, which is based on the replacement of indeterminate interval-type parameters with independent random variables with a uniform distribution. The extended Kalman filter (EKF) is used to solve the identification problem. The simulation results are presented.
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Smagin et al. (2025) studied this question.
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