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Chaos, Solitons and Fractals, 2021
Abstract In recent years, complexity-entropy causality plane, Shannon-Fisher information plane and Renyi-Tsalli entropy plane methods have been proposed to study one-dimensional nonlinear complex systems and widely applied in many fields. However, it is much less common for these definitions to extend to two-dimensional or higher-dimensional data ...
Pengjian Shang
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Abstract In recent years, complexity-entropy causality plane, Shannon-Fisher information plane and Renyi-Tsalli entropy plane methods have been proposed to study one-dimensional nonlinear complex systems and widely applied in many fields. However, it is much less common for these definitions to extend to two-dimensional or higher-dimensional data ...
Pengjian Shang
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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 ...
Hamed Azami, Javier Escudero
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Applied Acoustics, 2021
Abstract With a view to completing the fault diagnosis of rotating machinery efficiently and accurately, this paper presents a novel fault diagnosis model that combines multivariate hierarchical multiscale fluctuation dispersion entropy (MHMFDE), multi-cluster feature selection (MCFS) and gray wolf optimization-based kernel extreme learning machine ...
Fuming Zhou, Jun Han, Xiaoqiang Yang
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Abstract With a view to completing the fault diagnosis of rotating machinery efficiently and accurately, this paper presents a novel fault diagnosis model that combines multivariate hierarchical multiscale fluctuation dispersion entropy (MHMFDE), multi-cluster feature selection (MCFS) and gray wolf optimization-based kernel extreme learning machine ...
Fuming Zhou, Jun Han, Xiaoqiang Yang
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Entropy, 2021 International audienceTwo-dimensional fuzzy entropy, dispersion entropy, and their multiscale extensions (MFuzzyEn2D and MDispEn2D, respectively) have shown promising results for image classifications.
Anne Humeau-Heurtier +2 more
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Refined Composite Multiscale Dispersion Entropy and Its Application to Biomedical Signals [PDF]
IEEE Transactions on Biomedical Engineering, 2017 Objective: We propose a novel complexity measure to overcome the deficiencies of the widespread and powerful multiscale entropy (MSE), including, MSE values may be undefined for short signals, and MSE is slow for real-time applications.Methods: We ...
Hamed Azami +2 more
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Variable-Step Multiscale Fuzzy Dispersion Entropy: A Novel Metric for Signal Analysis
Entropy, 2023 Fuzzy dispersion entropy (FuzDE) is a newly proposed entropy metric, which combines the superior characteristics of fuzzy entropy (FE) and dispersion entropy (DE) in signal analysis.
Yuxing Li, Bingzhao Tang, Junxian Wu
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Entropy, 2023 Rotary machines often exhibit nonlinear behavior due to factors such as nonlinear stiffness, damping, friction, coupling effects, and defects. Consequently, their vibration signals display nonlinear characteristics.
Hamed Azami +2 more
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Entropy, 2021 Bearing vibration signals typically have nonlinear components due to their interaction and coupling effects, friction, damping, and nonlinear stiffness. Bearing faults affect the signal complexity at various scales.
Hamed Azami +2 more
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Multiscale Fluctuation-Based Dispersion Entropy and Its Applications to Neurological Diseases [PDF]
IEEE Access, 2019 Fluctuation-based dispersion entropy (FDispEn) is a new approach to estimate the dynamical variability of the fluctuations of signals. It is based on Shannon entropy and fluctuation-based dispersion patterns.
Zhuoqing Chang +2 more
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