• Corpus ID: 19387376

Permutation Entropies and Chaos

@inproceedings{Hawkins2015PermutationEA,
  title={Permutation Entropies and Chaos},
  author={Russell Stewart Hawkins},
  year={2015}
}
Permutation entropy is a metric used to quantify the regularity of a time series. Here I report on its application to the problem of characterizing the behavior of a few nonlinear dynamical systems, specifically the Duffing oscillator and the Tent and Logistic maps. Numerical results indicate that the permutation entropy can in principle be used to detemine the entropy rate of a system, and thus whether it is chaotic or not, but that in practice the convergence is slow. Additionally… 

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References

SHOWING 1-3 OF 3 REFERENCES
Permutation entropy: a natural complexity measure for time series.
TLDR
The method introduces complexity parameters for time series based on comparison of neighboring values and shows that its complexity behaves similar to Lyapunov exponents, and is particularly useful in the presence of dynamical or observational noise.
Permutation Excess Entropy and Mutual Information between the Past and Future
TLDR
It is shown that the permutation excess entropy is equal to the mutual information between two adjacent semi-infinite blocks in the space of orderings for finite-state stationary ergodic Markov processes.
Permutation Complexity in Dynamical Systems