Optimal Filtering of Linear System Driven by Fractional Brownian Motion

In this paper, we consider a continuous time filtering of a multi-dimensional Langevin stochastic differential system driven by a fractional Brownian motion process. It is shown that this filtering problem is equivalent to an optimal control problem involving convolutional integrals in its dynamical...

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Main Authors: Misiran, Masnita, Wu, C., Lu, Z., Teo, Kok Lay
Format: Journal Article
Published: Dynamic Publishers 2010
Subjects:
Online Access:http://hdl.handle.net/20.500.11937/9384
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author Misiran, Masnita
Wu, C.
Lu, Z.
Teo, Kok Lay
author_facet Misiran, Masnita
Wu, C.
Lu, Z.
Teo, Kok Lay
author_sort Misiran, Masnita
building Curtin Institutional Repository
collection Online Access
description In this paper, we consider a continuous time filtering of a multi-dimensional Langevin stochastic differential system driven by a fractional Brownian motion process. It is shown that this filtering problem is equivalent to an optimal control problem involving convolutional integrals in its dynamical system. Then, a novel approximation scheme is developed and applied to this optimal control problem. It yields a sequence of standard optimal control problems. The convergence of the approximate standard optimal control problem to the optimal control problem involving convolutional integrals in its system dynamics is established. Two numerical examples are solved by using the method proposed. The results obtained clearly demonstrate its efficiency and effectiveness.
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institution Curtin University Malaysia
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last_indexed 2025-11-14T06:25:14Z
publishDate 2010
publisher Dynamic Publishers
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spelling curtin-20.500.11937-93842017-01-30T11:12:21Z Optimal Filtering of Linear System Driven by Fractional Brownian Motion Misiran, Masnita Wu, C. Lu, Z. Teo, Kok Lay fractional Brownian motion approximation scheme convolutional integrals optimal control approximate optimal control computation linear filtering In this paper, we consider a continuous time filtering of a multi-dimensional Langevin stochastic differential system driven by a fractional Brownian motion process. It is shown that this filtering problem is equivalent to an optimal control problem involving convolutional integrals in its dynamical system. Then, a novel approximation scheme is developed and applied to this optimal control problem. It yields a sequence of standard optimal control problems. The convergence of the approximate standard optimal control problem to the optimal control problem involving convolutional integrals in its system dynamics is established. Two numerical examples are solved by using the method proposed. The results obtained clearly demonstrate its efficiency and effectiveness. 2010 Journal Article http://hdl.handle.net/20.500.11937/9384 Dynamic Publishers fulltext
spellingShingle fractional Brownian motion
approximation scheme
convolutional integrals
optimal control
approximate optimal control computation
linear filtering
Misiran, Masnita
Wu, C.
Lu, Z.
Teo, Kok Lay
Optimal Filtering of Linear System Driven by Fractional Brownian Motion
title Optimal Filtering of Linear System Driven by Fractional Brownian Motion
title_full Optimal Filtering of Linear System Driven by Fractional Brownian Motion
title_fullStr Optimal Filtering of Linear System Driven by Fractional Brownian Motion
title_full_unstemmed Optimal Filtering of Linear System Driven by Fractional Brownian Motion
title_short Optimal Filtering of Linear System Driven by Fractional Brownian Motion
title_sort optimal filtering of linear system driven by fractional brownian motion
topic fractional Brownian motion
approximation scheme
convolutional integrals
optimal control
approximate optimal control computation
linear filtering
url http://hdl.handle.net/20.500.11937/9384