Aimed to alleviate the influence of uncertainty in wind speed time series, a time adaptive filter based empirical mode decomposition (TVF-EMD) approach is used to decompose the original wind speed series into several intrinsic mode functions (IMFs).
In addition to the calculation reported in this article, we have also applied an ensemble empirical mode decomposition method and Bayesian approach to analyze the regional differences of climate indicators, and the patterns are approximately the same.
The proposed approach, empirical mode decomposition (EMD) and matching pursuit are respectively applied to analyzing a simulated faulty vibration and a simulated faulty gear vibration signal.
In the proposed approach, ensemble empirical mode decomposition (EEMD), a competitive multi-scale analysis tool, is first implemented to capture meaningful features hidden in the original market system.
Built on the proposed theoretical results and dynamic mode decomposition technique, a distributed data-driven approach is proposed for verification of the structural balance of large-scale multiplex signed networks without relying on the explicit knowledge on network topology.
In this context, our aim was to compare the ability of two stochastic approaches of blind source separation, namely independent component analysis (ICA) and canonical correlation analysis (CCA), and of two deterministic approaches namely empirical mode decomposition (EMD) and wavelet transform (WT) to remove muscle artifacts from EEG signals.
A novel approach for bidimensional empirical mode decomposition (BEMD) is proposed in this paper.
An integrated approach, consisting of empirical mode decomposition, Laplace wavelet correlation filtering, and wavelet finite element model, proposed by Dong et al. for rotor crack detection, was effective in identifying the position and the depth of different cracks [15].
The measured responses of the harvesters from the tests are presented and the use the harvesters for the purposes of structural health monitoring (SHM) is investigated using empirical mode decomposition analysis, following a bespoke data cleaning approach.
In this paper, we combine concepts of the generalized multiscale finite element method (GMsFEM) and mode decomposition methods to construct a robust global local approach for model reduction of flows in high-contrast porous media.
