Data assimilation approach to analysing systems of ordinary differential equations

The problem of parameter fitting for nonlinear oscillator models to noisy time series is addressed using a combination of Ensemble Kalman Filter and optimisation techniques. Encouraging preliminary results for acceptable sampling rates and noise levels are presented. Application to the understanding...

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Bibliographic Details
Published in2018 IEEE International Symposium on Circuits and Systems (ISCAS) pp. 1 - 5
Main Authors Arter, Wayne, Osojnik, Ana, Cartis, Coralia, Madho, Godwin, Jones, Chris, Tobias, Steven
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.05.2018
Subjects
Analytical models
Data assimilation
Data models
Mathematical model
Oscillators
Plasmas
Predictive models
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Summary:The problem of parameter fitting for nonlinear oscillator models to noisy time series is addressed using a combination of Ensemble Kalman Filter and optimisation techniques. Encouraging preliminary results for acceptable sampling rates and noise levels are presented. Application to the understanding and control of tokamak nuclear reactor operation is discussed.
ISSN:2379-447X
DOI:10.1109/ISCAS.2018.8351751