Results 11 to 20 of about 2,902,055 (272)

Ordinal synchronization: Using ordinal patterns to capture interdependencies between time series [PDF]

Chaos, Solitons and Fractals, 2019
We introduce Ordinal Synchronization ($OS$) as a new measure to quantify synchronization between dynamical systems. $OS$ is calculated from the extraction of the ordinal patterns related to two time series, their transformation into $D$-dimensional ordinal vectors and the adequate quantification of their alignment.
Jesus Ricardo Sevilla-Escoboza, Javier M Buldú   +1 more
exaly   +6 more sources

Exploring EEG Emotion Recognition through Complex Networks: Insights from the Visibility Graph of Ordinal Patterns

Applied Sciences
The construction of complex networks from electroencephalography (EEG) proves to be an effective method for representing emotion patterns in affection computing as it offers rich spatiotemporal EEG features associated with brain emotions.
Longxin Yao, Yun Lu, Mingjiang Wang, Yukun Qian, Heng Li   +4 more
doaj   +4 more sources

Ordinal analysis of lexical patterns [PDF]

Chaos: An Interdisciplinary Journal of Nonlinear Science, 2023
Words are fundamental linguistic units that connect thoughts and things through meaning. However, words do not appear independently in a text sequence. The existence of syntactic rules induces correlations among neighboring words. Using an ordinal pattern approach, we present an analysis of lexical statistical connections for 11 major languages.
David Sánchez, Luciano Zunino, Juan De Gregorio, Raúl Toral, Claudio Mirasso   +4 more
openaire   +6 more sources

Conditional entropy of ordinal patterns [PDF]

Physica D: Nonlinear Phenomena, 2014
In this paper we investigate a quantity called conditional entropy of ordinal patterns, akin to the permutation entropy. The conditional entropy of ordinal patterns describes the average diversity of the ordinal patterns succeeding a given ordinal pattern.
Anton Unakafov, Karsten Keller
exaly   +3 more sources

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
doaj   +5 more sources

Two-by-two ordinal patterns in art paintings. [PDF]

PNAS Nexus
Abstract 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, Pessa AAB, Zunino L, Rosso OA, Perc M, Ribeiro HV.   +5 more
europepmc   +5 more sources

Evaluating Methods for Detrending Time Series Using Ordinal Patterns, with an Application to Air Transport Delays [PDF]

Entropy
Functional networks have become a standard tool for the analysis of complex systems, allowing the unveiling of their internal connectivity structure while only requiring the observation of the system’s constituent dynamics.
Felipe Olivares, F. Javier Marín-Rodríguez, Kishor Acharya, Massimiliano Zanin   +3 more
doaj   +2 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, Inga Stolz, Karsten Keller   +2 more
doaj   +4 more sources

Continuous ordinal patterns: Creating a bridge between ordinal analysis and deep learning

Chaos: An Interdisciplinary Journal of Nonlinear Science, 2023
We introduce a generalization of the celebrated ordinal pattern approach for the analysis of time series, in which these are evaluated in terms of their distance to ordinal patterns defined in a continuous way. This allows us to naturally incorporate information about the local amplitude of the data and to optimize the ordinal pattern(s) to the problem
Massimiliano Zanin, Zanin, Massimiliano
openaire   +4 more sources

Wiggles and Curves: The Analysis of Ordinal Patterns

Problemy Zarządzania, 2016
Almost all social science data are analysed with variants of the General Linear Model (GLM): regression analyses, analyses of variance, factor analyses, path analyses and the like.
Warren Thorngate, Chunyun Ma
doaj   +2 more sources