Representing Entropy with Dispersion Sets [PDF]
Entropy, 2010 A novel representation of entropy is introduced, based on the heuristic concept of heat dispersion. To this end dispersion sets are defined, which describe both the heat transferred to a system and the associated entropy change.
Bernhard Kolarczyk
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Dispersion entropy for graph signals [PDF]
Chaos, Solitons & Fractals, 2023 We present a novel method, called Dispersion Entropy for Graph Signals, DEG, as a powerful tool for analysing the irregularity of signals defined on graphs. DEG generalises the classical dispersion entropy concept for univariate time series, enabling its
Fabila-Carrasco, John Stewart +6 more
core +3 more sources
Assessment of Outliers and Detection of Artifactual Network Segments Using Univariate and Multivariate Dispersion Entropy on Physiological Signals [PDF]
Entropy, 2021 Network physiology has emerged as a promising paradigm for the extraction of clinically relevant information from physiological signals by moving from univariate to multivariate analysis, allowing for the inspection of interdependencies between organ ...
Evangelos Kafantaris +3 more
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A New Method of Fault Feature Extraction Based on Hierarchical Dispersion Entropy
Shock and Vibration, 2021 In the process of fault feature extraction of rolling bearing, the feature information is difficult to be extracted fully. A novel method of fault feature extraction called hierarchical dispersion entropy is proposed in this paper.
Peng Chen, Xiaoqiang Zhao, HongMei Jiang
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Coarse-Graining Approaches in Univariate Multiscale Sample and Dispersion Entropy [PDF]
Entropy, 2018 The evaluation of complexity in univariate signals has attracted considerable attention in recent years. This is often done using the framework of Multiscale Entropy, which entails two basic steps: coarse-graining to consider multiple temporal scales, and evaluation of irregularity for each of those scales with entropy estimators.
Hamed Azami, Javier Escudero
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A Feature Extraction Method of Ship-Radiated Noise Based on Fluctuation-Based Dispersion Entropy and Intrinsic Time-Scale Decomposition [PDF]
Entropy, 2019 To improve the feature extraction of ship-radiated noise in a complex ocean environment, fluctuation-based dispersion entropy is used to extract the features of ten types of ship-radiated noise.
Zhaoxi Li, Yaan Li, Kai Zhang
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Augmentation of Dispersion Entropy for Handling Missing and Outlier Samples in Physiological Signal Monitoring [PDF]
Entropy, 2020 Entropy quantification algorithms are becoming a prominent tool for the physiological monitoring of individuals through the effective measurement of irregularity in biological signals.
Evangelos Kafantaris +3 more
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Dispersion entropy: A Measure of Irregularity for Graph Signals [PDF]
, 2023 We introduce a novel method, called Dispersion Entropy for Graph Signals, $DE_G$, as a powerful tool for analysing the irregularity of signals defined on graphs.
Fabila-Carrasco, John Stewart +2 more
core +4 more sources
Multivariate Multiscale Dispersion Entropy of Biomedical Times Series [PDF]
Entropy (Basel), 2019 Due to the non-linearity of numerous physiological recordings, non-linear analysis of multi-channel signals has been extensively used in biomedical engineering and neuroscience. Multivariate multiscale sample entropy (MSE - mvMSE) is a popular non-linear
Azami H, Fernández A, Escudero J.
europepmc +8 more sources
Sensors, 2021 One of the remaining challenges for the scientific-technical community is predicting preterm births, for which electrohysterography (EHG) has emerged as a highly sensitive prediction technique.
Félix Nieto-del-Amor +8 more
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