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

• 平田, 祥人

• Sato, Yuzuru

• Faranda, Davide

抄録

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 data set generated by non-autonomous dynamical systems.

収録刊行物

• Chaos: An Interdisciplinary Journal of Nonlinear Science

  Chaos: An Interdisciplinary Journal of Nonlinear Science 30 (10), 103103-, 2020-10

  American Institute of Physics

キーワード

• Applied Mathematics
• General Physics and Astronomy
• Mathematical Physics
• Statistical and Nonlinear Physics

詳細情報

• CRID: 1050009173185353600
• NII論文ID: 120007182859
• NII書誌ID: AA10811388
• DOI: 10.1063/5.0009450
• ISSN: 10897682
• ISSN: 10541500
• HANDLE: 2241/0002002407
• Web Site: https://tsukuba.repo.nii.ac.jp/records/2002407
• Web Site: https://pubs.aip.org/aip/cha/article-pdf/doi/10.1063/5.0009450/14627185/103103_1_online.pdf
• 本文言語コード: en
• 資料種別: journal article
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