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Deep learning for universal linear embeddings of nonlinear dynamics
Identifying coordinate transformations that make strongly nonlinear dynamics approximately linear has the potential to enable nonlinear prediction, estimation, and control using linear theory. The Koopman operator is a leading data-driven embedding, and its eigenfunctions provide intrinsic coordinat...
Autores principales: | Lusch, Bethany, Kutz, J. Nathan, Brunton, Steven L. |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6251871/ https://www.ncbi.nlm.nih.gov/pubmed/30470743 http://dx.doi.org/10.1038/s41467-018-07210-0 |
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