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Kernel learning for robust dynamic mode decomposition: linear and nonlinear disambiguation optimization
Research in modern data-driven dynamical systems is typically focused on the three key challenges of high dimensionality, unknown dynamics and nonlinearity. The dynamic mode decomposition (DMD) has emerged as a cornerstone for modelling high-dimensional systems from data. However, the quality of the...
| Autores principales: | , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
The Royal Society
2022
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9006118/ https://www.ncbi.nlm.nih.gov/pubmed/35450026 http://dx.doi.org/10.1098/rspa.2021.0830 |