Results 21 to 30 of about 23,305 (264)
on the Influence of Sampling on the Empirical Mode Decomposition [PDF]
2006 IEEE International Conference on Acoustics Speed and Signal Processing Proceedings, 2006 The rationale underlying the nonlinear Empirical Mode Decomposition method is intrinsically a continuous-time approach. The method can however only be applied in practice to discrete-time signals. EMD is obtained through iterating a basic nonlinear operator for which we derive an upper bound for the effects of sampling.
Gabriel Rilling, Patrick Flandrin
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Journal of Low Frequency Noise, Vibration and Active Control, 2021 In order to identify the nonlinear nonstationary pitting-wear fault signal of gears in gearbox, a new method of composite fault diagnosis for gearbox is proposed, which combines empirical mode decomposition with improved variational mode decomposition ...
Jingyue Wang +3 more
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International Journal of Distributed Sensor Networks, 2018 The bidimensional empirical mode decomposition algorithm is more suitable to handle image fusion than the traditional multi-scale decomposition methods in the image fusion area.
Pei Wang, Hui Fu, Ke Zhang
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A comparative study of single-channel signal processing methods in fetal phonocardiography.
PLoS ONE, 2022 Fetal phonocardiography is a non-invasive, completely passive and low-cost method based on sensing acoustic signals from the maternal abdomen. However, different types of interference are sensed along with the desired fetal phonocardiography.
Katerina Barnova +4 more
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A Comparative Study of Empirical and Variational Mode Decomposition on High Voltage Discharges
Electrica, 2018 Signal quality is the keyissue for maintaining effective power transmission in electrical networks. Inmost cases, a high voltage (HV) is transmitted in power systems to decreasepower loss.
Cengiz Polat Uzunoğlu
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Weak Signal Enhance Based on the Neural Network Assisted Empirical Mode Decomposition
Sensors, 2020 In order to enhance weak signals in strong noise background, a weak signal enhancement method based on EMDNN (neural network-assisted empirical mode decomposition) is proposed.
Kai Chen +3 more
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Research of partial discharge detection for XLPE cable
Gong-kuang zidonghua, 2014 In order to extract characteristics of partial discharge signals, the paper proposed an adaptive threshold algorithm for processing partial discharge data by using ensemble empirical mode decomposition method for analysis of XLPE cable partial discharge ...
TANG Zhongyu +3 more
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Empirical mode decomposition on surfaces
Graphical Models, 2012 Empirical Mode Decomposition (EMD) is a powerful tool for analysing non-linear and non-stationary signals, and has drawn a great deal of attentions in various areas. In this paper, we generalize the classical EMD from Euclidean space to the setting of surfaces represented as triangular meshes.
Hui Wang 0018 +4 more
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Empirical mode decomposition with shape-preserving spline interpolation
Results in Applied Mathematics, 2020 Empirical mode decomposition (EMD) is a popular, novel, user-friendly algorithm to decompose a given signal into its constituting components, utilizing spline interpolation.
Maria D. van der Walt
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Graph Empirical Mode Decomposition
, 2014 Publication in the conference proceedings of EUSIPCO, Lisbon, Portugal ...
Nicolas Tremblay +2 more
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