mode decomposition
Speech enhancement using empirical mode decomposition and the Teager–Kaiser energy operator
... signal decomposition method, called empirical mode decomposition (EMD), has been introduced by Huang et ...intrinsic mode functions ...
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Empirical Mode Decomposition in the Reduced-Order Modeling of Aeroelastic Systems
... Intrinsic Mode Functions (IMFs), derived from the Empirical Mode Decomposition (EMD), and the slow-flow model of a strongly nonlinear dynamical system 1,2,3 ...
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Dual PZT sizing for mode decomposition on a composite anisotropic plate
... sending back the reverse signal received by a given PZT, the input signal used in first place should be recovered. A damage potentially breaks this relation, allowing for its detection. This method has been validated on ...
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ISAR Image formation with a combined Empirical Mode Decomposition and Time-Frequency Representation
... to transformations or processing that map the signal into its TFR [5–7]. Recently, Empirical Mode Decomposition (EMD) has been introduced by Huang et al. [8] for analyzing data from non- stationary and ...
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Empirical Mode Decomposition for Noninvasive Atrial Fibrillation Dominant Frequency Estimation
... empirical mode decomposition (EEMD) [13] to noninvasively ex- tract atrial spectral information in patients suffering from ...pirical mode decomposition (EMD) [8], which uses em- pirical ...
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Multivariate Nonstationary Oscillation Simulation of Climate Indices with Empirical Mode Decomposition.
... Abstract The objective of the current study is to build a stochastic model to simulate climate indices that are teleconnected with the hydrologic regimes of large-scale water resources systems such as the Great Lakes ...
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2011 — Detection of pathologies in retina digital images an empirical mode decomposition approach
... empirical mode decomposition should be applied to other types of biomedical images such as brain magnetic resonance images, mammograms, skin, and prostate digital images in order to check the superiority of ...
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Stochastic simulation of nonstationary oscillation hydroclimatic processes using empirical mode decomposition.
... [ 1 ] Nonstationary oscillation (NSO) processes are observed in a number of hydroclimatic data series. Stochastic simulation models are useful to study the impacts of the climatic variations induced by NSO processes into ...
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Polymer electrolyte membrane fuel cell fault diagnosis based on empirical mode decomposition
... a b s t r a c t Diagnosis tool for water management is relevant to improve the reliability and lifetime of polymer electrolyte membrane fuel cells (PEMFCs). This paper presents a novel signal-based diagnosis approach, ...
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Normal mode decomposition and dispersive and nonlinear mixing in stratified fluids
... normal mode decomposition of the solutions to this linear system is performed in ...this decomposition is governed by a sequence of uncoupled dispersive perturbations of waves ...
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Turning Tangent Empirical Mode Decomposition: A Framework for Mono- and Multivariate Signals.
... Mpirical Mode Decomposition (EMD) was originally introduced in the late 1990’s to study water surface wave evolution ...Intrinsic Mode Functions, IMFs), plus a residue a N ...
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A wavelet-based mode decomposition compared to the EMD
... [3] N. E. Huang, Z. Shen, S. R. Long, M. L. Wu, H. H. Shih, Q. Zheng, N. C. Yen, C. C. Tung, and H. H. Liu The empirical mode decomposition and Hilbert spectrum for nonlinear and nonstationary time series ...
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Empirical Mode Decomposition of Multiple ECG Leads for Catheter Ablation Long-Term Outcome Prediction in Persistent Atrial Fibrillation
... empirical mode decomposition (EEMD) [14, 15] to obtain the intrinsic mode functions (IMFs) that compose the AF ECG signal without requiring any additional transformed ...
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Automated detection of circinate exudates in retina digital images using empirical mode decomposition and the entropy and uniformity of the intrinsic mode functions
... empirical mode decomposition (EMD) [13], an adaptive decomposition technique introduced for signal processing, was successfully applied for retina digital image processing and feature extraction for ...
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Automatic heart rate detection from FBG sensors using sensor fusion and enhanced empirical mode decomposition
... empirical mode decomposition with adaptive noise (CEEMDAN) and sensor fusion for automatic heart rate detection from a mat with embedded Fiber Bragg Grating (FBG) sensor ...
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Empirical Mode Decomposition (EMD) for multi-gate, multi-transducer Ultrasound Doppler fetal heart monitoring
... Empirical Mode Decomposition We have seen that the Autocorrelation FHR detection method is a good method to detect FHR in a normal ...empirical mode decomposition as an interesting alternative ...
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Prediction of climate nonstationary oscillation processes with empirical mode decomposition.
... decomposition method named empirical mode decomposition (EMD). Irregular oscillatory processes in a given variable can be extracted into a finite number of intrinsic mode functions with the ...
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An Adaptive Computation of Contour Representations for Mode Decomposition
... An Adaptive Computation of Contour Representations for Mode Decomposition Duong-Hung Pham, and Sylvain Meignen. Abstract—This letter addresses the problem of the detection and estimation of the modes of a ...
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Multivariate empirical mode decomposition and application to multichannel filtering
... Empirical Mode Decomposition (EMD) is an emerging topic in signal pro- cessing research, applied in various practical fields due in particular to its data-driven filter bank ...ward decomposition of ...
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Incremental dynamic mode decomposition: A reduced-model learner operating at the low-data limit
... Mode decomposition Nonlinear reduced modeling The present work aims at proposing a new methodology for learning reduced models from a small amount of ...
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