Articles | Volume 24, issue 1
Nonlin. Processes Geophys., 24, 9–22, 2017
https://doi.org/10.5194/npg-24-9-2017
Nonlin. Processes Geophys., 24, 9–22, 2017
https://doi.org/10.5194/npg-24-9-2017

Research article 16 Jan 2017

Research article | 16 Jan 2017

Estimating the state of a geophysical system with sparse observations: time delay methods to achieve accurate initial states for prediction

Zhe An et al.

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Cited articles

Abarbanel, H. D. I.: Analysis of Observed Chaotic Data, Springer, New York, 1996.
Abarbanel, H. D. I.: Predicting the Future: Completing Models of Observed Complex Systems, Springer-Verlag, New York, 2013.
Abarbanel, H. D. I., Creveling, D. R., Farsian, R., and Kostuk, M.: Dynamical State and Parameter Estimation, SIAM J. Appl. Dyn. Syst., 8, 1341–1381, 2009.
Aeyels, D.: Generic observability of differentiable systems, SIAM J. Control Optim., 19, 595–603, 1981a.
Aeyels, D.: On the number of samples necessary to achieve observability, Syst. Control Lett., 1, 92–94, 1981b.