Iterative Sparse Identification of Nonlinear Dynamics
In order to extract governing equations from time-series data, various approaches are proposed. Among those, sparse identification of nonlinear dynamics (SINDy) stands out as a successful method capable of modeling governing equations with a minimal number of terms, utilizing the principles of compr...
| 出版年: | IEEE Open Journal of Signal Processing |
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| 第一著者: | |
| フォーマット: | 論文 |
| 言語: | 英語 |
| 出版事項: |
IEEE
2024-01-01
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| 主題: | |
| オンライン･アクセス: | https://ieeexplore.ieee.org/document/10750024/ |