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Reconstructing bifurcation diagrams only from time-series data generated by electronic circuits in discrete-time dynamical systems
http://hdl.handle.net/10228/00007779
http://hdl.handle.net/10228/00007779d0d05280-10d1-4727-afdc-2d7809167234
名前 / ファイル | ライセンス | アクション |
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Item type | 学術雑誌論文 = Journal Article(1) | |||||||||||||||||||||
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公開日 | 2020-06-04 | |||||||||||||||||||||
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資源タイプ識別子 | http://purl.org/coar/resource_type/c_6501 | |||||||||||||||||||||
資源タイプ | journal article | |||||||||||||||||||||
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タイトル | Reconstructing bifurcation diagrams only from time-series data generated by electronic circuits in discrete-time dynamical systems | |||||||||||||||||||||
言語 | ||||||||||||||||||||||
言語 | eng | |||||||||||||||||||||
著者 |
Itoh, Y.
× Itoh, Y.× 上ノ原, 誠二
WEKO
27838
× Adachi, M.× 森江, 隆
WEKO
1615
× Aihara, K. |
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抄録 | ||||||||||||||||||||||
内容記述タイプ | Abstract | |||||||||||||||||||||
内容記述 | Bifurcation-diagram reconstruction estimates various attractors of a system without observing all of them but only from observing several attractors with different parameter values. Therefore, the bifurcation-diagram reconstruction can be used to investigate how attractors change with the parameter values, especially for real-world engineering and physical systems for which only a limited number of attractors can be observed. Although bifurcation diagrams of various systems have been reconstructed from time-series data generated in numerical experiments, the systems that have been targeted for reconstructing bifurcation diagrams from time series measured from physical phenomena so far have only been continuous-time dynamical systems. In this paper, we reconstruct bifurcation diagrams only from time-series data generated by electronic circuits in discrete-time dynamical systems with different parameter values. The generated time-series datasets are perturbed by dynamical noise and contaminated by observational noise. To reconstruct the bifurcation diagrams only from the time-series datasets, we use an extreme learning machine as a time-series predictor because it has a good generalization property. Hereby, we expect that the bifurcation-diagram reconstruction with the extreme learning machine is robust against dynamical noise and observational noise. For quantitatively verifying the robustness, the Lyapunov exponents of the reconstructed bifurcation diagrams are compared with those of the bifurcation diagrams generated in numerical experiments and by the electronic circuits. | |||||||||||||||||||||
書誌情報 |
Chaos 巻 30, p. 013128-1-013128-11, 発行日 2020-01-16 |
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出版者 | AIP Publishing | |||||||||||||||||||||
DOI | ||||||||||||||||||||||
関連タイプ | isIdenticalTo | |||||||||||||||||||||
識別子タイプ | DOI | |||||||||||||||||||||
関連識別子 | 10.1063/1.5119187 | |||||||||||||||||||||
NCID | ||||||||||||||||||||||
収録物識別子タイプ | NCID | |||||||||||||||||||||
収録物識別子 | AA10811388 | |||||||||||||||||||||
ISSN | ||||||||||||||||||||||
収録物識別子タイプ | ISSN | |||||||||||||||||||||
収録物識別子 | 1054-1500 | |||||||||||||||||||||
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収録物識別子タイプ | ISSN | |||||||||||||||||||||
収録物識別子 | 1089-7682 | |||||||||||||||||||||
著作権関連情報 | ||||||||||||||||||||||
権利情報 | Copyright (c) 2020 Author(s). | |||||||||||||||||||||
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権利情報 | Creative Commons Attribution (CC BY) license | |||||||||||||||||||||
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権利情報 | http://creativecommons.org/licenses/by/4.0/ | |||||||||||||||||||||
出版タイプ | ||||||||||||||||||||||
出版タイプ | VoR | |||||||||||||||||||||
出版タイプResource | http://purl.org/coar/version/c_970fb48d4fbd8a85 | |||||||||||||||||||||
査読の有無 | ||||||||||||||||||||||
値 | yes | |||||||||||||||||||||
研究者情報 | ||||||||||||||||||||||
https://hyokadb02.jimu.kyutech.ac.jp/html/339_ja.html | ||||||||||||||||||||||
論文ID(連携) | ||||||||||||||||||||||
10349720 | ||||||||||||||||||||||
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8311 | ||||||||||||||||||||||
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識別子タイプ | DOI | |||||||||||||||||||||
関連識別子 | https://doi.org/10.1063/1.5119187 | |||||||||||||||||||||
関連名称 | https://doi.org/10.1063/1.5119187 |