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Article Dans Une Revue Chaos: An Interdisciplinary Journal of Nonlinear Science Année : 2020

Permutations uniquely identify states and unknown external forces in non-autonomous dynamical systems

Résumé

It has been shown that a permutation can uniquely identify the joint set of an initial condition and a non-autonomous external force realization added to the deterministic system in given time series data. We demonstrate that our results can be applied to time series forecasting as well as the estimation of common external forces. Thus, permutations provide a convenient description for a time series dataset generated by non-autonomous dynamical systems.
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Dates et versions

hal-02949037 , version 1 (25-09-2020)

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Yoshito Hirata, Yuzuru Sato, Davide Faranda. Permutations uniquely identify states and unknown external forces in non-autonomous dynamical systems. Chaos: An Interdisciplinary Journal of Nonlinear Science, 2020, 30, pp.103103. ⟨10.1063/5.0009450⟩. ⟨hal-02949037⟩
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