Statistical inference in the Duffing System with the Unscented Kalman Filter

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

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract / Description of output

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 languageEnglish
Title of host publicationProceedings of the 32nd International Workshop on Statistical Modelling
EditorsMarco Grzegorczyk, Giacomo Ceoldo
Pages119-122
Publication statusPublished - 1 Jul 2017

Keywords / Materials (for Non-textual outputs)

  • Bayesian filtering
  • Unscented Kalman Filte
  • Chaotic dynamical system
  • Parameter estimation

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