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Yang, Q., Sing-Long, C. A., Reed, E. J. (2020) Rapid data-driven model reduction of nonlinear dynamical systems including chemical reaction networks using ℓ1-regularization. Chaos: An Interdisciplinary Journal of Nonlinear Science, 30 (5) 53122pp. doi:10.1063/1.5139463

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Reference TypeJournal (article/letter/editorial)
TitleRapid data-driven model reduction of nonlinear dynamical systems including chemical reaction networks using ℓ1-regularization
JournalChaos: An Interdisciplinary Journal of Nonlinear Science
AuthorsYang, Q.Author
Sing-Long, C. A.Author
Reed, E. J.Author
Year2020 (May)Volume30
Issue5
PublisherAIP Publishing
DOIdoi:10.1063/1.5139463Search in ResearchGate
Generate Citation Formats
Mindat Ref. ID13208061Long-form Identifiermindat:1:5:13208061:5
GUID0
Full ReferenceYang, Q., Sing-Long, C. A., Reed, E. J. (2020) Rapid data-driven model reduction of nonlinear dynamical systems including chemical reaction networks using ℓ1-regularization. Chaos: An Interdisciplinary Journal of Nonlinear Science, 30 (5) 53122pp. doi:10.1063/1.5139463
Plain TextYang, Q., Sing-Long, C. A., Reed, E. J. (2020) Rapid data-driven model reduction of nonlinear dynamical systems including chemical reaction networks using ℓ1-regularization. Chaos: An Interdisciplinary Journal of Nonlinear Science, 30 (5) 53122pp. doi:10.1063/1.5139463
In(2020, May) Chaos: An Interdisciplinary Journal of Nonlinear Science Vol. 30 (5) AIP Publishing

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