Arrhythmia ECG Noise Reduction by Ensemble Empirical Mode Decomposition [PDF]
Sensors, 2010 A novel noise filtering algorithm based on ensemble empirical mode decomposition (EEMD) is proposed to remove artifacts in electrocardiogram (ECG) traces.
Kang-Ming Chang
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Fault Diagnosis of Rotating Machinery Based on an Adaptive Ensemble Empirical Mode Decomposition [PDF]
Sensors, 2013 The vibration based signal processing technique is one of the principal tools for diagnosing faults of rotating machinery. Empirical mode decomposition (EMD), as a time-frequency analysis technique, has been widely used to process vibration signals of ...
Yaguo Lei +3 more
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Bird Call Identification Using Ensemble Empirical Mode Decomposition
Shock and VibrationBirds are iconic species of the environment. Bird monitoring can be achieved by collecting recordings of the calls of wild birds and later identifying the species. A new approach suggested in this study involves the application of ensemble empirical mode
Jingxuan Liu, Hailan Chen
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Estimation of Heart Rate and Respiratory Rate from PPG Signal Using Complementary Ensemble Empirical Mode Decomposition with both Independent Component Analysis and Non-Negative Matrix Factorization [PDF]
Sensors, 2020 This paper proposes a framework combining the complementary ensemble empirical mode decomposition with both the independent component analysis and the non-negative matrix factorization for estimating both the heart rate and the respiratory rate from the ...
Ruisheng Lei +3 more
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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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Morphological Filter-Assisted Ensemble Empirical Mode Decomposition [PDF]
Mathematical Problems in Engineering, 2018 In the ensemble empirical mode decomposition (EEMD) algorithm, different realizations of white noise are added to the original signal as dyadic filter banks to overcome the mode mixing problems of empirical mode decomposition (EMD). However, not all the components in white noise are necessary, and the superfluous components will introduce additional ...
Xiaohang Zhou, Deshan Shan, Qiao Li
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Analysis of Vehicle Platform Vibration Based on Empirical Mode Decomposition
Shock and Vibration, 2021 Vehicle platform vibration (VPV) directly affects the measurement accuracy of precise measuring instrument (PMI) fixed on it. In order to reduce the influences of VPV on measurement accuracy, it is necessary to perform vibration isolation between vehicle
Chengwu Shen +5 more
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IEEE Access, 2021 Numerous studies employ multi-scale decomposition to improve the prediction performance of neural networks, but the grounds for selecting the decomposition algorithm are not explained, and the effects of decomposition algorithms on other performance of ...
Haichao Huang +4 more
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Improving the prediction accuracy of river inflow using two data pre-processing techniques coupled with data-driven model [PDF]
PeerJ, 2019 River inflow prediction plays an important role in water resources management and power-generating systems. But the noises and multi-scale nature of river inflow data adds an extra layer of complexity towards accurate predictive model.
Hafiza Mamona Nazir +4 more
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Filtering of surface EMG using ensemble empirical mode decomposition [PDF]
Medical Engineering & Physics, 2013 Surface electromyogram (EMG) is often corrupted by three types of noises, i.e. power line interference (PLI), white Gaussian noise (WGN), and baseline wandering (BW). A novel framework based primarily on empirical mode decomposition (EMD) was developed to reduce all the three noise contaminations from surface EMG.
Xu, Zhang, Ping, Zhou
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