Results 1 to 10 of about 13,661 (279)
Bearing Fault Diagnosis Based on Multiscale Permutation Entropy and Support Vector Machine
Entropy, 2012 Bearing fault diagnosis has attracted significant attention over the past few decades. It consists of two major parts: vibration signal feature extraction and condition classification for the extracted features.
Shuen-De Wu +2 more
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Application of Permutation Entropy and Permutation Min-Entropy in Multiple Emotional States Analysis of RRI Time Series [PDF]
Entropy, 2018 This study’s aim was to apply permutation entropy (PE) and permutation min-entropy (PME) over an RR interval time series to quantify the changes in cardiac activity among multiple emotional states. Electrocardiogram (ECG) signals were recorded under six emotional states (neutral, happiness, sadness, anger, fear, and disgust) in 60 healthy subjects at a
Licai Yang +2 more
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Permutation Entropy for Graph Signals [PDF]
IEEE Transactions on Signal and Information Processing over Networks, 2022 Entropy metrics (for example, permutation entropy) are nonlinear measures of irregularity in time series (one-dimensional data). Some of these entropy metrics can be generalised to data on periodic structures such as a grid or lattice pattern (two-dimensional data) using its symmetry, thus enabling their application to images.
John Stewart Fabila-Carrasco +2 more
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The asymptotic distribution of the permutation entropy [PDF]
Chaos: An Interdisciplinary Journal of Nonlinear Science, 2023 Ordinal patterns serve as a robust symbolic transformation technique, enabling the unveiling of latent dynamics within time series data. This methodology involves constructing histograms of patterns, followed by the calculation of both entropy and statistical complexity—an avenue yet to be fully understood in terms of its statistical properties.
A. A. Rey +3 more
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Generalized Gaussian Distribution Improved Permutation Entropy: A New Measure for Complex Time Series Analysis [PDF]
EntropyTo enhance the performance of entropy algorithms in analyzing complex time series, generalized Gaussian distribution improved permutation entropy (GGDIPE) and its multiscale variant (MGGDIPE) are proposed in this paper.
Kun Zheng +4 more
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Permutation Entropy and Its Main Biomedical and Econophysics Applications: A Review
Entropy, 2012 Entropy is a powerful tool for the analysis of time series, as it allows describing the probability distributions of the possible state of a system, and therefore the information encoded in it.
Massimiliano Zanin +2 more
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Proceedings of the International Florida Artificial Intelligence Research Society Conference, 2021 The estimation of the qualitative behaviour of fractional Brownian motion is an important topic for modelling real-world applications. Permutation entropy is a well-known approach to quantify the complexity of univariate time series in a scalar-valued ...
Marisa Mohr +2 more
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Generalized weighted permutation entropy
Chaos: An Interdisciplinary Journal of Nonlinear Science, 2022 A novel heuristic approach is proposed here for time series data analysis, dubbed Generalized weighted permutation entropy, which amalgamates and generalizes beyond their original scope two well established data analysis methods: Permutation entropy and Weighted permutation entropy.
Darko Stosic +3 more
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On the automatic parameter selection for permutation entropy [PDF]
Chaos: An Interdisciplinary Journal of Nonlinear Science, 2020 Permutation Entropy (PE) is a cost effective tool for summarizing the complexity of a time series. It has been used in many applications including damage detection, disease forecasting, detection of dynamical changes, and financial volatility analysis.
Audun Myers, Firas A. Khasawneh
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Entropy, 2023 The study focuses on the fault signals of rolling bearings, which are characterized by nonlinearity, periodic impact, and low signal-to-noise ratio.
Qiang Yuan +5 more
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