Data-driven discovery of partial differential equations

We propose a sparse regression method capable of discovering the governing partial differential equation(s) of a given system by time series measurements in the spatial domain. The regression framework relies on sparsity-promoting techniques to select the nonlinear and partial derivative terms of th...

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Detalles Bibliográficos
Autores principales: Rudy, Samuel H., Brunton, Steven L., Proctor, Joshua L., Kutz, J. Nathan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Association for the Advancement of Science 2017
Materias:
Research Articles
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5406137/
https://www.ncbi.nlm.nih.gov/pubmed/28508044
http://dx.doi.org/10.1126/sciadv.1602614

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5406137/
https://www.ncbi.nlm.nih.gov/pubmed/28508044
http://dx.doi.org/10.1126/sciadv.1602614

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