Adaptive prediction of stochastic differential equations with unknown parameters | Vestnik Tomskogo gosudarstvennogo universiteta. Upravlenie, vychislitelnaja tehnika i informatika – Tomsk State University Journal of Control and Computer Science. 2017. № 38. DOI: 10.17223/19988605/38/3

Adaptive prediction of stochastic differential equations with unknown parameters

This paper proposes adaptive predictors of continuous-time dynamic systems with unknown parameters. Predictors are based on the truncated parameter estimators. In particular, there are considered the Ornstein-Uhlenbeck process and one-parameter stochastic delay differential equation. In this paper the truncated estimation method is first applied to continuous-time systems. Asymptotic and non-asymptotic properties of the predictors are investigated. There is also found the rate of convergence of the second moment of a prediction error to its minimum value.

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Keywords

дифференциальные уравнения с запаздыванием, процесс Орнштейна-Уленбека, системы с непрерывным временем, усеченное оценивание, адаптивные прогнозы, Ornstein-Uhlenbeck process, delay differential equations, prediction, continuous-time dynamic systems, truncated estimation

Authors

Name	Organization	E-mail
Dogadova Tatiana V.	Tomsk State University	aurora1900@mail.ru
Vasiliev Vyacheslav A.	Tomsk State University	vas@mail.tsu.ru

Всего: 2

References

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