Assessing the predictability of nonlinear dynamics under smooth parameter changes
Author:
Affiliation:
1. Department of Civil and Environmental Engineering, MIT, Cambridge, MA, USA
2. DCI, LLC, 201 Spear Street, Suite 250, San Francisco, CA, USA
3. Scripps Institution of Oceanography, University of California San Diego, La Jolla, CA, USA
Abstract
Publisher
The Royal Society
Subject
Biomedical Engineering,Biochemistry,Biomaterials,Bioengineering,Biophysics,Biotechnology
Link
https://royalsocietypublishing.org/doi/pdf/10.1098/rsif.2019.0627
Reference34 articles.
1. SECTION OF PLANETARY SCIENCES: THE PREDICTABILITY OF HYDRODYNAMIC FLOW*,†
2. Nonlinear time-series analysis revisited
3. Discovering governing equations from data by sparse identification of nonlinear dynamical systems
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