Results 11 to 20 of about 197,948 (294)
Development of novel hybrid models for the prediction of Covid-19 in Kuwait
Kuwait Journal of Science, 2021 The first case of coronavirus 2019 (Covid-19) in Kuwait was reported on February 24, 2020, and then day by day cases of Covid-19 keep on increasing.
Ahmad Aldousari +3 more
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IET Signal Processing, 2023 Electrocardiogram (ECG) is the most extensively applied diagnostic approach for heart diseases. However, an ECG signal is a weak bioelectrical signal and is easily disturbed by baseline wander, powerline interference, and muscle artefacts, which make ...
Yaru Yue +3 more
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Iraqi Geological Journal, 2023 This study aims to use the Empirical Mode Decomposition for reducing the noise of passive seismic signals recorded across seismic event recorded at Kirkuk station which is one of the Iraqi Meteorological Organization and Seismology data, where ...
Zainab Mahmmoud, Ali Al-Rahim
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Energies, 2021 Accurately predicting surface vibration signals of diesel engines is the key to evaluating the operation quality of diesel engines. Based on an improved empirical mode decomposition and extreme learning machine algorithm, the characteristics of diesel ...
Yan Shen +3 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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Applied Sciences, 2022 Multicomponent seismic exploration provides more wavefield information for imaging complex subsurface structures and predicting reservoirs. Ground roll is strongly coherent noise in land multicomponent seismic data and exhibits similar features, which ...
Liying Xiao, Zhifu Zhang, Jianjun Gao
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Empirical Mode Decomposition as a Filter Bank [PDF]
IEEE Signal Processing Letters, 2004 Empirical mode decomposition (EMD) has recently been pioneered by Huang et al. for adaptively representing nonstationary signals as sums of zero-mean amplitude modulation frequency modulation components. In order to better understand the way EMD behaves in stochastic situations involving broadband noise, we report here on numerical experiments based on
Flandrin, Patrick +2 more
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Theoretical Analysis of Empirical Mode Decomposition [PDF]
Symmetry, 2018 This work suggests a theoretical principle about the oscillation signal decomposition, which is based on the requirement of a pure oscillation component, in which the mean zero is extracted from the signal. Using this principle, the validity and robustness of the empirical mode decomposition (EMD) method are first proved mathematically.
Hengqing Ge +4 more
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Noise-Assisted Multivariate Empirical Mode Decomposition Based Emotion Recognition
Electrica, 2018 Emotion state detection or emotion recognition cuts across different disciplines because of the many parameters that embrace the brain's complex neural structure, signal processing methods, and pattern recognition algorithms.
Pınar Özel +2 more
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Enhancing Performance of Single-Channel SSVEP-Based Visual Acuity Assessment via Mode Decomposition
IEEE Transactions on Neural Systems and Rehabilitation Engineering, 2023 This study aimed to improve the performance of single-channel steady-state visual evoked potential (SSVEP)-based visual acuity assessment by mode decomposition methods.
Xiaowei Zheng +3 more
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