Classification of Motor Imagery BCI Using Multivariate Empirical Mode Decomposition [PDF]
IEEE Transactions on Neural Systems and Rehabilitation Engineering, 2013 Brain electrical activity recorded via electroencephalogram (EEG) is the most convenient means for brain-computer interface (BCI), and is notoriously noisy. The information of interest is located in well defined frequency bands, and a number of standard frequency estimation algorithms have been used for feature extraction.
Park, Cheolsoo +4 more
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On the behavior of EMD and MEMD in presence of symmetric alpha-stable noise [PDF]
, 2014 EmpiricalMode Decomposition (EMD) and its extended versions such as Multivariate EMD (MEMD) are data-driven techniques that represent nonlinear and non-stationary data as a sum of a finite zero-mean AM-FM components referred to as Intrinsic Mode ...
NOLAN, John +4 more
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Atmosphere, 2023 This study analyzed the multifractal characteristics of daily reference evapotranspiration (ETo) time series of the Tabriz and Urmia stations of northwestern Iran and its cross-correlation with five other meteorological variables.
Adarsh Sankaran +4 more
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Multivariate enhanced adaptive empirical Fourier decomposition and its application in rolling bearing fault diagnosis [PDF]
, 2023 Enhanced adaptive empirical Fourier decomposition EAEFD is a recently developed single channel signal separation algorithm which has attracted increasing attention for diagnosing localized rolling bearing failures Even though the EAEFD approach can ...
Cao, S +11 more
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A Complex Empirical Mode Decomposition for Multivariant Traffic Time Series
Electronics, 2023 Data-driven modeling methods have been widely used in many applications or studies of traffic systems with complexity and chaos. The empirical mode decomposition (EMD) family provides a lightweight analytical method for non-stationary and non-linear data.
Guochen Shen, Lei Zhang
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Designing a multi-stage multivariate empirical mode decomposition coupled with ant colony optimization and random forest model to forecast monthly solar radiation [PDF]
, 2019 Solar energy is an alternative renewable energy resource that has the potential of cleanly addressing the increasing demand for electricity in the modern era to overcome future energy crises.
Kwan, Paul +3 more
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Elastic Net Regression and Empirical Mode Decomposition for Enhancing the Accuracy of the Model Selection [PDF]
International Journal of Mathematical, Engineering and Management Sciences, 2021 Elastic net (ELNET) regression is a hybrid statistical technique used for regularizing and selecting necessary predictor variables that have a strong effect on the response variable and deal with multicollinearity problem when it exists between the ...
Abdullah S. Al-Jawarneh +2 more
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Chaotic signals denoising using empirical mode decomposition inspired by multivariate denoising [PDF]
, 2020 Empirical mode decomposition (EMD) is an effective noise reduction method to enhance the noisy chaotic signal over additive noise. In this paper, the intrinsic mode functions (IMFs) generated by EMD are thresholded using multivariate denoising ...
Fadhil Sahib Hasan, Hasan, Fadhil Sahib
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A novel method to identify the flow pattern of oil–water two-phase flow
Journal of Petroleum Exploration and Production Technology, 2020 This paper presents a novel method combining extreme learning machine (ELM) and multiple empirical mode decomposition (MEMD) to identify flow patterns of oil–water two-phase flow. The proposed method can recognize accurately five typical flow patterns of
Zhong-Cheng Li, Chun-Ling Fan
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IEEE Access, 2020 This paper describes a novel multichannel signal denoising approach based on multivariate variational mode decomposition (MVMD). MVMD is the extended version of the variational mode decomposition (VMD) algorithm for multichannel data sets.
Peipei Cao, Huali Wang, Kaijie Zhou
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