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arXiv · 2009.02547

Ordinal spectrum: a frequency domain characterization of complex time series

Mario Chavez·Johann H. Martinez
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Abstract

Although classical spectral analysis is a natural approach to characterise linear systems, it cannot describe a chaotic dynamics. Here, we propose the ordinal spectrum, a method based on a spectral transformation of symbolic sequences, to characterise the complexity of a time series. In contrasts with other nonlinear mapping functions (e.g. the state-space reconstruction) the proposed representation is a natural approach to distinguish, in a frequency domain, a chaotic behavior. We test the method in different synthetic and real-world data. Our results suggest that the proposed approach may provide new insights into the non-linear oscillations observed in different real data.

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Mario Chavez, Johann H. Martinez. 2020-09-05. Ordinal spectrum: a frequency domain characterization of complex time series. https://arxiv.org/abs/2009.02547

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