Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
1864373 | Physics Letters A | 2014 | 5 Pages |
Abstract
Transferring information from observations to models of complex systems may meet impediments when the number of observations at any observation time is not sufficient. This is especially so when chaotic behavior is expressed. We show how to use time-delay embedding, familiar from nonlinear dynamics, to provide the information required to obtain accurate state and parameter estimates. Good estimates of parameters and unobserved states are necessary for good predictions of the future state of a model system. This method may be critical in allowing the understanding of prediction in complex systems as varied as nervous systems and weather prediction where insufficient measurements are typical.
Related Topics
Physical Sciences and Engineering
Physics and Astronomy
Physics and Astronomy (General)
Authors
Daniel Rey, Michael Eldridge, Mark Kostuk, Henry D.I. Abarbanel, Jan Schumann-Bischoff, Ulrich Parlitz,