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Oscillation Mode Assessment in Power System Using Multivariate Variational Mode Decomposition
IECON 2021 – 47th Annual Conference of the IEEE Industrial Electronics Society, 2021The identification of electromechanical modes in the power system has been researched extensively in the last decade. Nonlinear nonstationary techniques like variational mode decomposition (VMD) are much effective in determining mode parameters. However, these methods experiment with single-channel data and while computing for other channels needs ...
S. Rahul, Sunitha Rajan, V. M. Akhil
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Monthly ship price forecasting based on multivariate variational mode decomposition
Engineering Applications of Artificial Intelligence, 2023Accurate and reliable ship price forecasts can assist shipping firms, investors, and other participants to withstand risks and make profits in a highly volatile shipping market. Considering the nonlinear behavior and sophisticated interrelationship of the shipping market, in this paper, a novel multiscale and multivariable methodology based on ...
Zicheng Wang +3 more
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An EMG Gesture Recognition Method based on Multivariate Variational Mode Decomposition
2021 4th International Conference on Advanced Electronic Materials, Computers and Software Engineering (AEMCSE), 2021Surface electromyography(sEMG) can reflect the state of muscle activity which has important application value in human-computer interaction, prosthetic control and clinical diagnosis. In this paper, a gesture recognition method based on convolutional neural network(CNN) as well as multivariate variational mode decomposition(MVMD) is proposed.
Kun Yang +3 more
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Multivariate Variational Mode Decomposition based Analysis on Stock Sectors
2021The price of a single stock is seldom independent. It has been known to brokers and fund managers, that, they heavily influence each other. Portfolios are built, on the premise of minimizing such dependencies between stocks. There have been several efforts to quantify these dependencies, predominantly using conventional statistics and correlations ...
Silpa Balagopal +3 more
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Time-varying system identification using variational mode decomposition
Structural Control and Health Monitoring, 2018 A new time-varying system identification approach is proposed in this paper by using variational mode decomposition. The newly developed variational mode decomposition technique can decompose the measured responses into a limited number of intrinsic mode
Yong Xia, Hong Hao, Xiangyu Wang
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Multivariate Variational Mode Decomposition based approach for Blink Removal from EEG Signal
2020 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops), 2020Electroencephalography (EEG) signals contain ocular artifacts which degrades the overall performance of any neuro-engineering based analysis or applications like brain computer interfaces. In general, independent component analysis (ICA) is used for removing blinks. However, that requires expert intervention.
Rahul Gavas +4 more
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Grouped Multivariate Variational Mode Decomposition With Application to EEG Analysis
IEEE Transactions on Biomedical EngineeringIn this paper, a novel extended form of multivariate variational mode decomposition (MVMD) method to multigroup data named as grouped MVMD (GMVMD) is proposed. GMVMD is distinct from MVMD as it extracts common frequencies with strong correlations among regional channels.Firstly, GMVMD utilizes a new clustering algorithm named as frequencies grouping ...
Jiawei Jian +6 more
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Measurement Science and Technology, 2022
Abstract Multivariate variational mode decomposition (MVMD) is a novel extension of variational mode decomposition (VMD) for multi-channel data sets. It decomposes multi-component and multi-channel signals into multivariate modulated oscillations crossing different center frequencies and limited bandwidths with ...
Zhaolun Li +3 more
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Abstract Multivariate variational mode decomposition (MVMD) is a novel extension of variational mode decomposition (VMD) for multi-channel data sets. It decomposes multi-component and multi-channel signals into multivariate modulated oscillations crossing different center frequencies and limited bandwidths with ...
Zhaolun Li +3 more
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2020 International Conference on Sensing, Measurement & Data Analytics in the era of Artificial Intelligence (ICSMD), 2020
The bearing failure diagnosis methods based upon variational mode decomposition (VMD) have been researched extensively in recent years. However, these methods are only capable of dealing with single channel data, in which the amount of information is limited and the anti-interference ability needs to be further enhanced.
Qiuyu Song +6 more
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The bearing failure diagnosis methods based upon variational mode decomposition (VMD) have been researched extensively in recent years. However, these methods are only capable of dealing with single channel data, in which the amount of information is limited and the anti-interference ability needs to be further enhanced.
Qiuyu Song +6 more
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Mechanomyography signals processing method using multivariate variational mode decomposition
2021 14th International Symposium on Computational Intelligence and Design (ISCID), 2021Chenlei Xie +3 more
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