Results 31 to 40 of about 189,338 (155)
Inferring long memory processes in the climate network via ordinal pattern analysis [PDF]
, 2011 We use ordinal patterns and symbolic analysis to construct global climate networks and uncover long and short term memory processes. The data analyzed is the monthly averaged surface air temperature (SAT field) and the results suggest that the time ...
Barreiro, Marcelo +2 more
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20 years of ordinal patterns: Perspectives and challenges
Europhysics Letters, 2022 Abstract In 2002, in a seminal article, Bandt and Pompe proposed a new methodology for the analysis of complex time series, now known as Ordinal Analysis. The ordinal methodology is based on the computation of symbols (known as ordinal patters) which are defined in terms of the temporal ordering of data points in a time series, and whose
Leyva Callejas, Inmaculada +4 more
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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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Ordinal patterns in the Duffing oscillator: Analyzing powers of characterization [PDF]
Chaos: An Interdisciplinary Journal of Nonlinear Science, 2021 Ordinal patterns are a time-series data analysis tool used as a preliminary step to construct the permutation entropy, which itself allows the same characterization of dynamics as chaotic or regular as more theoretical constructs such as the Lyapunov exponent.
Ivan Gunther +2 more
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On Quasi Ordinal Diagram Systems [PDF]
Electronic Proceedings in Theoretical Computer Science, 2019 The purposes of this note are the following two; we first generalize Okada-Takeuti's well quasi ordinal diagram theory, utilizing the recent result of Dershowitz-Tzameret's version of tree embedding theorem with gap conditions.
Mitsuhiro Okada, Yuta Takahashi
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Teaching Ordinal Patterns to a Computer: Efficient Encoding Algorithms Based on the Lehmer Code
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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Ordinal Classification: Working Definition and Detection of Ordinal Structures
IEEE Access, 2020 Ordinal classification (OC) is an important niche of supervised pattern recognition, in which the classes constitute an ordinal structure. In general, the ordinal structure can be identified, either according to the natural occurrence of the current task
Peter Bellmann, Friedhelm Schwenker
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A binary neural k-nearest neighbour technique [PDF]
, 2005 K-Nearest Neighbour (k-NN) is a widely used technique for classifying and clustering data. K-NN is effective but is often criticised for its polynomial run-time growth as k-NN calculates the distance to every other record in the data set for each record ...
Austin, J., Hodge, V.J.
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Entropy, 2023 Individual subjects’ ratings neither are metric nor have homogeneous meanings, consequently digital- labeled collections of subjects’ ratings are intrinsically ordinal and categorical.
Emanuela Furfaro, Fushing Hsieh
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Bandt-Pompe symbolization dynamics for time series with tied values: A data-driven approach [PDF]
, 2018 In 2002, Bandt and Pompe [Phys. Rev. Lett. 88, 174102 (2002)] introduced a successfully symbolic encoding scheme based on the ordinal relation between the amplitude of neighboring values of a given data sequence, from which the permutation entropy can be
Alejandro C. Frery +8 more
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