Sparse identification of Lagrangian for nonlinear dynamical systems via proximal gradient method
Abstract The autonomous distillation of physical laws only from data is of great interest in many scientific fields. Data-driven modeling frameworks that adopt sparse regression techniques, such as sparse identification of nonlinear dynamics (SINDy) and its modifications, are developed to resolve di...
| Published in: | Scientific Reports |
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| Main Authors: | , |
| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2023-05-01
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| Online Access: | https://doi.org/10.1038/s41598-023-34931-0 |