Deep learning for universal linear embeddings of nonlinear dynamics
It is often advantageous to transform a strongly nonlinear system into a linear one in order to simplify its analysis for prediction and control. Here the authors combine dynamical systems with deep learning to identify these hard-to-find transformations.
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| Auteurs principaux: | , , |
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| Format: | article |
| Langue: | EN |
| Publié: |
Nature Portfolio
2018
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| Sujets: | |
| Accès en ligne: | https://doaj.org/article/d72f7d260a5d4c2a905fed768a9492b8 |
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