Observation-parameterised risk-sensitive state estimation with correlated noise processes

P. Florchinger; W. P. Malcolm

doi:10.1109/CDC.2004.1430361

Observation-parameterised risk-sensitive state estimation with correlated noise processes

P. Florchinger^*, W. P. Malcolm

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

In this article we consider risk sensitive filtering and smoothing for a nonlinear scalar-valued dynamical system with correlated state and observer noise processes. The model we consider is an Itô diffusion state process observed through a Wiener process. Using gauge transformation techniques, we compute an observation-parameterised risk sensitive filter for the system just described. An important feature of the filters we compute is that no stochastic integrations are involved. An observation-parameterised smoother is also computed.

Original language	English
Title of host publication	2004 43rd IEEE Conference on Decision and Control (CDC)
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	2118-2122
Number of pages	5
ISBN (Print)	0780386825
DOIs	https://doi.org/10.1109/CDC.2004.1430361
Publication status	Published - 2004
Event	2004 43rd IEEE Conference on Decision and Control (CDC) - Nassau, Bahamas Duration: 14 Dec 2004 → 17 Dec 2004

Publication series

Name	Proceedings of the IEEE Conference on Decision and Control
Volume	2
ISSN (Print)	0743-1546
ISSN (Electronic)	2576-2370

Conference

Conference	2004 43rd IEEE Conference on Decision and Control (CDC)
Country/Territory	Bahamas
City	Nassau
Period	14/12/04 → 17/12/04

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10.1109/CDC.2004.1430361

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Florchinger, P., & Malcolm, W. P. (2004). Observation-parameterised risk-sensitive state estimation with correlated noise processes. In 2004 43rd IEEE Conference on Decision and Control (CDC) (pp. 2118-2122). Article WeB08.6 (Proceedings of the IEEE Conference on Decision and Control; Vol. 2). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CDC.2004.1430361

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title = "Observation-parameterised risk-sensitive state estimation with correlated noise processes",

abstract = "In this article we consider risk sensitive filtering and smoothing for a nonlinear scalar-valued dynamical system with correlated state and observer noise processes. The model we consider is an It{\^o} diffusion state process observed through a Wiener process. Using gauge transformation techniques, we compute an observation-parameterised risk sensitive filter for the system just described. An important feature of the filters we compute is that no stochastic integrations are involved. An observation-parameterised smoother is also computed.",

keywords = "Filtering, Risk Sensitive Filtering, Smoothing, Stochastic Flows, Stochastic Integral Equations, The Cauchy Problem",

author = "P. Florchinger and Malcolm, {W. P.}",

year = "2004",

doi = "10.1109/CDC.2004.1430361",

language = "English",

isbn = "0780386825",

series = "Proceedings of the IEEE Conference on Decision and Control",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "2118--2122",

booktitle = "2004 43rd IEEE Conference on Decision and Control (CDC)",

address = "United States",

note = "2004 43rd IEEE Conference on Decision and Control (CDC) ; Conference date: 14-12-2004 Through 17-12-2004",

}

Florchinger, P & Malcolm, WP 2004, Observation-parameterised risk-sensitive state estimation with correlated noise processes. in 2004 43rd IEEE Conference on Decision and Control (CDC)., WeB08.6, Proceedings of the IEEE Conference on Decision and Control, vol. 2, Institute of Electrical and Electronics Engineers Inc., pp. 2118-2122, 2004 43rd IEEE Conference on Decision and Control (CDC), Nassau, Bahamas, 14/12/04. https://doi.org/10.1109/CDC.2004.1430361

Observation-parameterised risk-sensitive state estimation with correlated noise processes. / Florchinger, P.; Malcolm, W. P.
2004 43rd IEEE Conference on Decision and Control (CDC). Institute of Electrical and Electronics Engineers Inc., 2004. p. 2118-2122 WeB08.6 (Proceedings of the IEEE Conference on Decision and Control; Vol. 2).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Malcolm, W. P.

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N2 - In this article we consider risk sensitive filtering and smoothing for a nonlinear scalar-valued dynamical system with correlated state and observer noise processes. The model we consider is an Itô diffusion state process observed through a Wiener process. Using gauge transformation techniques, we compute an observation-parameterised risk sensitive filter for the system just described. An important feature of the filters we compute is that no stochastic integrations are involved. An observation-parameterised smoother is also computed.

AB - In this article we consider risk sensitive filtering and smoothing for a nonlinear scalar-valued dynamical system with correlated state and observer noise processes. The model we consider is an Itô diffusion state process observed through a Wiener process. Using gauge transformation techniques, we compute an observation-parameterised risk sensitive filter for the system just described. An important feature of the filters we compute is that no stochastic integrations are involved. An observation-parameterised smoother is also computed.

KW - Filtering

KW - Risk Sensitive Filtering

KW - Smoothing

KW - Stochastic Flows

KW - Stochastic Integral Equations

KW - The Cauchy Problem

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T3 - Proceedings of the IEEE Conference on Decision and Control

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EP - 2122

BT - 2004 43rd IEEE Conference on Decision and Control (CDC)

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2004 43rd IEEE Conference on Decision and Control (CDC)

Y2 - 14 December 2004 through 17 December 2004

ER -

Observation-parameterised risk-sensitive state estimation with correlated noise processes

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