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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Generalized Ordinal Patterns and the KS-Entropy [PDF]
Entropy, 2021 Ordinal patterns classifying real vectors according to the order relations between their components are an interesting basic concept for determining the complexity of a measure-preserving dynamical system. In particular, as shown by C. Bandt, G.
Tim Gutjahr, Karsten Keller
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Ordinal Spectrum: Mapping Ordinal Patterns into Frequency Domain [PDF]
EntropyClassical spectral analysis characterizes linear systems effectively but often fails to reveal the nonlinear temporal structure of chaotic dynamics. We introduce the ordinal spectrum, a frequency-domain characterization derived from the ordinal-pattern ...
Mario Chavez, Johann H. Martínez
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Change-Point Detection Using the Conditional Entropy of Ordinal Patterns [PDF]
Entropy, 2018 This paper is devoted to change-point detection using only the ordinal structure of a time series. A statistic based on the conditional entropy of ordinal patterns characterizing the local up and down in a time series is introduced and investigated.
Anton M. Unakafov, Karsten Keller
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A new network representation for time series analysis from the perspective of combinatorial property of ordinal patterns [PDF]
Heliyon, 2023 Revealing system behavior from observed time series is a fundamental problem worthy of in-depth study and exploration, and has attracted extensive attention in a wide range of fields due to its wide application values.
Yun Lu +6 more
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Using the Information Provided by Forbidden Ordinal Patterns in Permutation Entropy to Reinforce Time Series Discrimination Capabilities [PDF]
Entropy, 2020 Despite its widely tested and proven usefulness, there is still room for improvement in the basic permutation entropy (PE) algorithm, as several subsequent studies have demonstrated in recent years. Some of these new methods try to address the well-known
David Cuesta-Frau
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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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Surrogate Data Preserving All the Properties of Ordinal Patterns up to a Certain Length [PDF]
Entropy, 2019 We propose a method for generating surrogate data that preserves all the properties of ordinal patterns up to a certain length, such as the numbers of allowed/forbidden ordinal patterns and transition likelihoods from ordinal patterns into others.
Yoshito Hirata +2 more
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Teaching Ordinal Patterns to a Computer: Efficient Encoding Algorithms Based on the Lehmer Code [PDF]
Entropy, 2019 Ordinal patterns are the common basis of various techniques used in the study of dynamical systems and nonlinear time series analysis. The present article focusses on the computational problem of turning time series into sequences of ordinal patterns. In
Sebastian Berger +3 more
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Two-by-two ordinal patterns in art paintings. [PDF]
PNAS NexusAbstract Quantitative analysis of visual arts has recently expanded to encompass a more extensive array of artworks due to the availability of large-scale digitized art collections. Consistent with formal analyses by art historians, many of these studies highlight the significance of encoding spatial structures within artworks to enhance
Tarozo MM +5 more
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