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Efficient nonlinear filtering of a singularly perturbed stochastic hybrid system

Part of: Qualitative theory Stochastic processes Nonlinear dynamics Miscellaneous topics - Partial differential equations Stochastic analysis

Published online by Cambridge University Press:  01 November 2011

Jun H. Park ,
Boris Rozovskii  and
Richard B. Sowers
Jun H. Park
Affiliation:
182 George Street, Providence, RI 02912, USA (email: jun_park@brown.edu)
Boris Rozovskii
Affiliation:
182 George Street, Providence, RI 02912, USA (email: boris_rozovsky@brown.edu)
Richard B. Sowers
Affiliation:
1409 W. Green Street, Urbana, IL 61801, USA (email: r-sowers@illinois.edu)

Abstract

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Our focus in this work is to investigate an efficient state estimation scheme for a singularly perturbed stochastic hybrid system. As stochastic hybrid systems have been used recently in diverse areas, the importance of correct and efficient estimation of such systems cannot be overemphasized. The framework of nonlinear filtering provides a suitable ground for on-line estimation. With the help of intrinsic multiscale properties of a system, we obtain an efficient estimation scheme for a stochastic hybrid system.

MSC classification

Secondary: 60H15: Stochastic partial differential equations 35R60: Partial differential equations with randomness, stochastic partial differential equations 60G35: Signal detection and filtering 34C29: Averaging method 70K65: Averaging of perturbations
Type
Research Article
Information
LMS Journal of Computation and Mathematics , Volume 14 , 2011 , pp. 254 - 270
Copyright
Copyright © London Mathematical Society 2011

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