Accurate state and parameter estimation in nonlinear systems with sparse observations

TitleAccurate state and parameter estimation in nonlinear systems with sparse observations
Publication TypeJournal Article
Year of Publication2014
AuthorsRey D., Eldridge M., Kostuk M., Abarbanel H.DI, Schumann-Bischoff J., Parlitz U.
JournalPhysics Letters A
Volume378
Pagination869-873
Date Published2014/02
Type of ArticleArticle
ISBN Number0375-9601
Accession NumberWOS:000332816900003
KeywordsData assimilation; flow; identification; model; number; observability; Synchronization; system; time series analysis; time-series
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. (C) 2014 Elsevier B.V. All rights reserved.

DOI10.1016/j.physleta.2014.01.027
Short TitlePhys. Lett. A
Student Publication: 
No
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