Results 231 to 240 of about 16,203 (295)

Grouped Multivariate Variational Mode Decomposition With Application to EEG Analysis

IEEE Transactions on Biomedical Engineering, 2023
In 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, Duanpo Wu, Jiuwen Cao, Fang Dong 0003, Junbiao Liu, Danping Wang, Shuchang Zhang   +6 more
openaire   +3 more sources

Self-Adaptive Multivariate Variational Mode Decomposition and Its Application for Bearing Fault Diagnosis

IEEE Transactions on Instrumentation and Measurement, 2022
In actual engineering scenarios, multichannel datasets that contain complete information contribute to better accuracy of bearing fault diagnosis. Multivariate variational mode decomposition (MVMD), as an extension of variational mode decomposition (VMD),
Qiuyu Song, Xingxing Jiang, Shuang Wang, Jianfeng Guo, Weiguo Huang, Zhongkui Zhu   +5 more
openaire   +2 more sources

Fuzzy Multivariate Variational Mode Decomposition With Applications in EEG Analysis

IEEE Transactions on Fuzzy Systems
This article introduces a novel extension of the multivariate variational mode decomposition (MVMD) method, termed fuzzy MVMD (FMVMD), designed to enhance alignment information extraction.
Hongkai Tang, Xun Yang 0001, Yixuan Yuan, Pierre-Paul Vidal, Danping Wang, Jiuwen Cao, Duanpo Wu   +6 more
openaire   +2 more sources

Oscillation Mode Assessment in Power System Using Multivariate Variational Mode Decomposition

IECON 2021 – 47th Annual Conference of the IEEE Industrial Electronics Society, 2021
The 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
openaire   +1 more source

Carbon Emission Price Point-Interval Forecasting Based on Multivariate Variational Mode Decomposition and Attention-Lstm Model

Applied Soft Computing, 2023
Liling Zeng, Huanling Hu, Huajun Tang, Xuejing Zhang, Dabin Zhang   +4 more
openaire   +2 more sources

Robust structural modal identification using multivariate variational mode decomposition

Journal of Civil Structural Health Monitoring
Mehulkumar Lakhadive, Shivank Mittal, Ayan Sadhu   +2 more
openaire   +2 more sources

An EMG Gesture Recognition Method based on Multivariate Variational Mode Decomposition

2021 4th International Conference on Advanced Electronic Materials, Computers and Software Engineering (AEMCSE), 2021
Surface 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, Manjin Xu, Xiaotong Yang, Yueming Chen   +3 more
openaire   +1 more source

Multi-channel MCG signals filtering method based on multivariate variational mode decomposition

Biomedical Signal Processing and Control
Kun Yang, Tiedong Xu, Deng Pan, Zhidan Zhang, Hai Wang, Xiangyan Kong   +5 more
semanticscholar   +3 more sources

Multivariate Variational Mode Decomposition based Analysis on Stock Sectors

2021
The 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, Vijay Krishna Menon, E. A. Gopalakrishnan, K. P. Soman   +3 more
openaire   +1 more source

An Early Chatter Detection Method Based on Multivariate Variational Mode Decomposition and Chatter Correlation Factor

IEEE/ASME Transactions on Mechatronics, 2022
Machining chatter is a self-excited vibration between the tool and the workpiece that affects surface quality and productivity. In this article, we propose a novel approach for early detection of machining chatter based on multivariate variational mode ...
Yezhong Lu, Haifeng Ma, Yuxin Sun, Zhanqiang Liu, Qinghua Song   +4 more
openaire   +2 more sources