Adaptive prediction of stochastic differential equations with unknown parameters

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Adaptive prediction of stochastic differential equations with unknown parameters	494 KB	Adobe Acrobat PDF	Read	Download
DOI Доступ к ресурсу на сайте издателя			10.17223/19988605/38/3

Title: Adaptive prediction of stochastic differential equations with unknown parameters
Title: Адаптивное прогнозирование стохастических систем с непрерывным временем
Creator: Dogadova, T. V.
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Vasiliev, Vyacheslav A.
Date: 2017
DOI: 10.17223/19988605/38/3
Description: 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.