Ordinal Pattern Dependence in the Context of Long-Range Dependence [PDF]
Entropy, 2021 Ordinal pattern dependence is a multivariate dependence measure based on the co-movement of two time series. In strong connection to ordinal time series analysis, the ordinal information is taken into account to derive robust results on the dependence ...
Ines Nüßgen, Alexander Schnurr
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Ordinal pattern-based change point detection [PDF]
TestAbstract The ordinal patterns of a fixed number of consecutive values in a time series are the spatial ordering of these values. Counting how often a specific ordinal pattern occurs in a time series provides important insights into the properties of the time series.
Annika Betken
exaly +9 more sources
Algorithmics, Possibilities and Limits of Ordinal Pattern Based Entropies [PDF]
Entropy, 2019 The study of nonlinear and possibly chaotic time-dependent systems involves long-term data acquisition or high sample rates. The resulting big data is valuable in order to provide useful insights into long-term dynamics.
Albert B. Piek +2 more
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Ordinal Pattern Based Entropies and the Kolmogorov–Sinai Entropy: An Update [PDF]
Entropy, 2020 Different authors have shown strong relationships between ordinal pattern based entropies and the Kolmogorov−Sinai entropy, including equality of the latter one and the permutation entropy, the whole picture is however far from being complete. This
Tim Gutjahr, Karsten Keller
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Including the Magnitude Variability of a Signal in the Ordinal Pattern Analysis [PDF]
EntropyOne of the most popular and innovative methods to analyse signals is by using Ordinal Patterns (OPs). The OP encoding is based on transforming a (univariate) signal into a symbolic sequence of OPs, where each OP represents the number of permutations ...
Melvyn Tyloo +2 more
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Segmentation Method for Ship-Radiated Noise Using the Generalized Likelihood Ratio Test on an Ordinal Pattern Distribution [PDF]
Entropy, 2020 Due to the diversity of ship-radiated noise (SRN), audio segmentation is an essential procedure in the ship statuses/categories identification. However, the existing segmentation methods are not suitable for the SRN because of the lack of prior knowledge.
Lei He +3 more
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Extracting Robust Biomarkers From Multichannel EEG Time Series Using Nonlinear Dimensionality Reduction Applied to Ordinal Pattern Statistics and Spectral Quantities [PDF]
Frontiers in Physiology, 2021 In this study, ordinal pattern analysis and classical frequency-based EEG analysis methods are used to differentiate between EEGs of different age groups as well as individuals.
Inga Kottlarz +15 more
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Ordinal Patterns, Entropy, and EEG [PDF]
Entropy, 2014 In this paper we illustrate the potential of ordinal-patterns-based methods for analysis of real-world data and, especially, of electroencephalogram (EEG) data. We apply already known (empirical permutation entropy, ordinal pattern distributions) and new
Karsten Keller +2 more
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Capturing synchronization with complexity measure of ordinal pattern transition network constructed by crossplot [PDF]
Royal Society Open Science, 2023 To evaluate the synchronization of bivariate time series has been a hot topic, and a number of measures have been proposed. In this work, by introducing the ordinal pattern transition network into the crossplot, a new method for measuring the ...
Xiaobi Chen +7 more
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Short-term prediction through ordinal patterns [PDF]
Royal Society Open Science, 2021 Prediction in natural environments is a challenging task, and there is a lack of clarity around how a myopic organism can make short-term predictions given limited data availability and cognitive resources.
Yair Neuman, Yochai Cohen, Boaz Tamir
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