Exploring functional connectivity at different timescales with multivariate mode decomposition [PDF]
Frontiers in NeuroscienceThis paper explores an alternative way for analyzing static Functional Connectivity (FC) in functional Magnetic Resonance Imaging (fMRI) data across multiple timescales using a class of adaptive frequency-based methods referred to as Multivariate Mode ...
Manuel Morante +2 more
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Remote Sensing, 2023 Radio-echo sounding (RES) is widely used for polar ice sheet detection due to its wide coverage and high efficiency. The multivariate variational mode decomposition (MVMD) algorithm for the processing of RES data is an improvement to the variational mode
Yuhan Chen +4 more
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New achievements on daily reference evapotranspiration forecasting: Potential assessment of multivariate signal decomposition schemes [PDF]
Ecological Indicators, 2023 Reference evapotranspiration (ETo) is a vital climate parameter affecting plants' water use. ETo can generate large deficits in soil moisture and runoff in different regions and seasons, leading to uncertainties in drought warning systems.
Mumtaz Ali +8 more
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Mode decomposition-based time-varying phase synchronization for fMRI [PDF]
NeuroImage, 2022 Recently, there has been significant interest in measuring time-varying functional connectivity (TVC) between different brain regions using resting-state functional magnetic resonance imaging (rs-fMRI) data.
Hamed Honari, Martin A. Lindquist
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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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A Novel Multivariate Cutting Force-Based Tool Wear Monitoring Method Using One-Dimensional Convolutional Neural Network [PDF]
Sensors, 2022 Tool wear condition monitoring during the machining process is one of the most important considerations in precision manufacturing. Cutting force is one of the signals that has been widely used for tool wear condition monitoring, which contains the ...
Xu Yang +4 more
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Seismic attenuation estimation using multivariate variational mode decomposition
Frontiers in Earth Science, 2022 A seismic attenuation estimation approach is proposed based on multivariate variational mode decomposition (MVMD). MVMD, as a multivariable or multichannel signal processing tool, can extract several predefined multivariable modulation oscillations from ...
Jun-Zhou Liu +9 more
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A Novel EMG-Based Hand Gesture Recognition Framework Based on Multivariate Variational Mode Decomposition [PDF]
Sensors, 2021 Surface electromyography (sEMG) is a kind of biological signal that records muscle activity noninvasively, which is of great significance in advanced human-computer interaction, prosthetic control, clinical therapy, and biomechanics.
Kun Yang +4 more
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Fault Detection and Isolation of MEMS IMU Array Based on WOA-MVMD-GLT [PDF]
MicromachinesThe stable and accurate output of the inertial measurement unit array (IMU) of a micro-electro-mechanical system (MEMS) is the key to ensuring the data fusion of the MEMS IMU array.
Hanyan Li +4 more
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Fault Diagnosis of Wind Turbine Gearbox Based on Improved Multivariate Variational Mode Decomposition and Ensemble Refined Composite Multivariate Multiscale Dispersion Entropy [PDF]
EntropyWind turbine planetary gearboxes have complex structures and operating environments, which makes it difficult to extract fault features effectively. In addition, it is difficult to achieve efficient fault diagnosis.
Xin Xia, Xiaolu Wang, Weilin Chen
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