State Space Reconstruction Parameters in the Analysis of Chaotic Time Series - the Role of the Time Window Length

Details State Space Reconstruction Parameters in the Analysis of Chaotic Time Series - the Role of the Time Window Length State Space Reconstruction Parameters in the Analysis of Chaotic Time Series - the Role of the Time Window Length

1996-02-29

arxiv.org/abs/comp-gas/9602002v1

Nonlinear Sciences

Cellular Automata and Lattice Gases

20 pages including 23 Postscript figures, uses epsfig.sty and amssymb.sty, to be published in Physica D

Scientific paper

The most common state space reconstruction method in the analysis of chaotic time series is the Method of Delays (MOD). Many techniques have been suggested to estimate the parameters of MOD, i.e. the time delay $\tau$ and the embedding dimension $m$. We discuss the applicability of these techniques with a critical view as to their validity, and point out the necessity of determining the overall time window length, $\tau_w$, for successful embedding. Emphasis is put on the relation between $\tau_w$ and the dynamics of the underlying chaotic system, and we suggest to set $\tau_w \geq \tau_p$, the mean orbital period; $\tau_p$ is approximated from the oscillations of the time series. The procedure is assessed using the correlation dimension for both synthetic and real data. For clean synthetic data, values of $\tau_w$ larger than $\tau_p$ always give good results given enough data and thus $\tau_p$ can be considered as a lower limit ($\tau_w \geq \tau_p$). For noisy synthetic data and real data, an upper limit is reached for $\tau_w$ which approaches $\tau_p$ for increasing noise amplitude.

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