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Tracing initial conditions, historical evolutionary path and parameters of chaotic processes from a short segment of scalar time series

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  • Lu, Fangfang
  • Xu, Daolin
  • Wen, Guilin

Abstract

An iterative optimization method is used to uncover unobserved initial state (t=0), historical evolutionary path (t0). Given the system structure, we can precisely estimate the model parameters, recover the trajectory components unobserved, identify the state of all variables at the beginning (t=t0) of the observed time series, and trace the historical evolution of the system back to a long time interval (0⩽t

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  • Lu, Fangfang & Xu, Daolin & Wen, Guilin, 2005. "Tracing initial conditions, historical evolutionary path and parameters of chaotic processes from a short segment of scalar time series," Chaos, Solitons & Fractals, Elsevier, vol. 24(1), pages 265-271.
    • Handle: RePEc:eee:chsofr:v:24:y:2005:i:1:p:265-271
    DOI: 10.1016/j.chaos.2004.09.030
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    1. John F. Y. Brookfield, 2001. "Predicting the future," Nature, Nature, vol. 411(6841), pages 999-999, June.
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