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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Detalles Bibliográficos
Autores principales: Bethany Lusch, J. Nathan Kutz, Steven L. Brunton
Formato: article
Lenguaje:EN
Publicado: Nature Portfolio 2018
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Acceso en línea:https://doaj.org/article/d72f7d260a5d4c2a905fed768a9492b8
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