Statistical inference in the Duffing System with the Unscented Kalman Filter

Michela Eugenia Pasetto; Dirk Husmeier; Umberto Noè; Alessandra Luati

Statistical inference in the Duffing System with the Unscented Kalman Filter

Michela Eugenia Pasetto, Dirk Husmeier, Umberto Noè, Alessandra Luati

School of Philosophy, Psychology and Language Sciences

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

Abstract

We investigate the accuracy of inference in a chaotic dynamical sys- tem (Duffing oscillator) with the Unscented Kalman Filter, and quantify the dependence on the sample size, the signal to noise ratio and the initialization.

Original language	English
Title of host publication	Proceedings of the 32nd International Workshop on Statistical Modelling
Editors	Marco Grzegorczyk, Giacomo Ceoldo
Pages	119-122
Publication status	Published - 1 Jul 2017

Keywords / Materials (for Non-textual outputs)

Bayesian filtering
Unscented Kalman Filte
Chaotic dynamical system
Parameter estimation

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https://iwsm2017.webhosting.rug.nl/IWSM_2017_V2.pdf

Cite this

@inproceedings{2a5ff6dbf9e04347a48de79a3a85344b,

title = "Statistical inference in the Duffing System with the Unscented Kalman Filter",

abstract = "We investigate the accuracy of inference in a chaotic dynamical sys- tem (Duffing oscillator) with the Unscented Kalman Filter, and quantify the dependence on the sample size, the signal to noise ratio and the initialization.",

keywords = "Bayesian filtering, Unscented Kalman Filte, Chaotic dynamical system, Parameter estimation",

author = "Pasetto, {Michela Eugenia} and Dirk Husmeier and Umberto No{\`e} and Alessandra Luati",

year = "2017",

month = jul,

day = "1",

language = "English",

pages = "119--122",

editor = "Marco Grzegorczyk and Giacomo Ceoldo",

booktitle = "Proceedings of the 32nd International Workshop on Statistical Modelling",

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T1 - Statistical inference in the Duffing System with the Unscented Kalman Filter

AU - Pasetto, Michela Eugenia

AU - Husmeier, Dirk

AU - Noè, Umberto

AU - Luati, Alessandra

PY - 2017/7/1

Y1 - 2017/7/1

N2 - We investigate the accuracy of inference in a chaotic dynamical sys- tem (Duffing oscillator) with the Unscented Kalman Filter, and quantify the dependence on the sample size, the signal to noise ratio and the initialization.

AB - We investigate the accuracy of inference in a chaotic dynamical sys- tem (Duffing oscillator) with the Unscented Kalman Filter, and quantify the dependence on the sample size, the signal to noise ratio and the initialization.

KW - Bayesian filtering

KW - Unscented Kalman Filte

KW - Chaotic dynamical system

KW - Parameter estimation

M3 - Conference contribution

SP - 119

EP - 122

BT - Proceedings of the 32nd International Workshop on Statistical Modelling

A2 - Grzegorczyk, Marco

A2 - Ceoldo, Giacomo

ER -

Statistical inference in the Duffing System with the Unscented Kalman Filter

Abstract

Keywords / Materials (for Non-textual outputs)

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Cite this