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

Fangfang Lu, Daolin Xu and Guilin Wen

Chaos, Solitons & Fractals, 2005, vol. 24, issue 1, 265-271

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⩽tDate: 2005
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Persistent link: https://EconPapers.repec.org/RePEc:eee:chsofr:v:24:y:2005:i:1:p:265-271

DOI: 10.1016/j.chaos.2004.09.030

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