Ordinal patterns in the Duffing oscillator: Analyzing powers of characterization

Ordinal patterns are a time-series data analysis tool used as preliminary step to construct the permutation entropy, which itself allows same characterization of dynamics chaotic or regular more theoretical constructs such Lyapunov exponent. However, ordinal store strictly information than entropy exponents. We present results working with Duffing oscillator showing that reflect changes in dynamical symmetry is invisible other measures, even entropy. find these at given parameter values correlated change stability neighboring parameters, suggests novel predictive capability for this technique.