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Identification of parameters of discrete stochastic systems with unknown inputs based on an information filtering algorithm
A.V. Tsyganov1

1 Department of Higher Mathematics, Ulyanovsk State University of Education,
Lenin square 4/5, Ulyanovsk, 432071, Russia

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DOI: 10.18287/COJ1872

Article ID: 1872

Language: English

Abstract:
The paper considers the problem of parameter identification of discrete linear stochastic systems in the state space. An identification criterion is proposed for systems with unknown inputs based on the information version of the Gillijns and De Moor algorithm. We apply this criterion to identify the diffusion coefficient of a one-dimensional diffusion model with unknown boundary conditions of the first kind. The results of computer modeling validate the presented approach.

Keywords:
discrete linear stochastic systems, parameter identification, unknown exogenous inputs, information filtering, identification criterion, diffusion model.

Acknowledgements:
The work was carried out under the Supplementary Agreement № 073-03-2025-066/1 dated March 19, 2025, to the Agreement on granting subsidies from the federal budget for financial support of the fulfillment of state assignments to provide public services (works) № 073-03-2025-066 dated January 16, 2025, concluded between Ulyanovsk State Pedagogical University and the Ministry of Education of the Russian Federation.

Citation:
Tsyganov AV. Identification of parameters of discrete stochastic systems with unknown inputs based on an information filtering algorithm. Computer Optics 2026; 50(4): 1872. doi: 10.18287/COJ1872.

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