Exploiting the impact of ordering patterns in the Fisher-Shannon complexity plan

Abstract: The Fisher-Shannon complexity plane is a powerful tool that represents complex dynamics in a two-dimensional plane. It locates a dynamical system based upon its entropy and its Fisher Information Measure (FIM). It has been recently shown that, by using ordinal patterns to compute permutation entropy and FIM, this plane unveils inner details of the structure underlying the complex and chaotic dynamics of a system. In order to compute FIM, the order of the patterns is very relevant. We analyze in detail the impact of the sorting protocol used to calculate FIM using ordinal patterns. We show the importance of a suitable choice, which can lead to saving computational resources, but also to unveil details of the dynamics not accessible to other sorting protocols. Our results agree with previous research, and common characteristic fingerprints are found for the different chaotic maps studied. Our analysis also reveals the fractal behavior of the chaotic maps studied. We extract some underlying symmetries that allow us to simulate the behavior on the complexity plane for a wide range of the control parameters in the chaotic regimes.