Results 11 to 20 of about 3,492,245 (278)

Time-Domain Electromagnetic Noise Suppression Using Multivariate Variational Mode Decomposition

Remote Sensing
Noise suppression is essential in time-domain electromagnetic (TDEM) data processing and interpretation. TDEM data are typically in broadband signal, which makes it difficult to separate the signal in the whole frequency band.
Kang Xing, Shiyan Li, Zhijie Qu, Xiaojuan Zhang   +3 more
doaj   +3 more sources

GPR Energy Attribute Slices Based on Multivariate Variational Mode Decomposition and Teager–Kaiser Energy Operator

Remote Sensing, 2022
The GPR signals appear nonlinear and nonstationary during propagation. To evaluate the nonstationarity, the empirical mode decomposition (EMD) and its modifications have been proposed to localize the variations of energy and frequency components over ...
Xuebing Zhang, Yuxiang Qin, Zhengkun Hu, Xin Hu, Xuan Feng, Yuan Chai   +5 more
doaj   +4 more sources

Noise-Assisted Multivariate Variational Mode Decomposition [PDF]

ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2021
The variational mode decomposition (VMD) is a widely applied optimization-based method, which analyzes non-stationary signals concurrently. Correspondingly, its recently proposed multivariate extension, i.e., MVMD, has shown great potentials in analyzing multichannel signals.
Zisou, Charilaos A., Apostolidis, Georgios K., Hadjileontiadis, Leontios J.   +2 more
openaire   +4 more sources

Variational mode decomposition based random forest model for solar radiation forecasting: New emerging machine learning technology

Energy Reports, 2021
Forecasting of solar radiation (Radn) can provide an insight vision for the amount of green and friendly energy sources. Owing to the non-linearity and non-stationarity challenges caused by meteorological variables in forecasting Radn, a variational mode
Mumtaz Ali, Ramendra Prasad, Yong Xiang, Mohsin Khan, Aitazaz Ahsan Farooque, Tianrui Zong, Zaher Mundher Yaseen   +6 more
doaj   +2 more sources

Multichannel Signal Denoising Using Multivariate Variational Mode Decomposition With Subspace Projection [PDF]

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
doaj   +3 more sources

Airborne Radio-Echo Sounding Data Denoising Using Particle Swarm Optimization and Multivariate Variational Mode Decomposition

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, Sixin Liu, Kun Luo, Lijuan Wang, Xueyuan Tang   +4 more
doaj   +2 more sources

Motor Imagery BCI Classification Based on Multivariate Variational Mode Decomposition

IEEE Transactions on Emerging Topics in Computational Intelligence, 2022
In this article, a novel computer-aided diagnosis framework is proposed for the classification of motor imagery (MI) electroencephalogram (EEG) signals. First, a multivariate variational mode decomposition (MVMD) method was employed to obtain joint modes in frequency scale across all channels.
Muhammad Tariq Sadiq, Xiaojun Yu 0001, Zhaohui Yuan, Muhammad Zulkifal Aziz, Naveed ur Rehman, Weiping Ding 0001, Gaoxi Xiao   +6 more
openaire   +4 more sources

Short-time variational mode decomposition [PDF]

Variational mode decomposition (VMD) and its extensions like Multivariate VMD (MVMD) decompose signals into ensembles of band-limited modes with narrow central frequencies using Fourier transformations.
Liang, Tong, Kushihashi, Yasuhiro, Cao, Pengfei, Jia, Hao, Grau Saldes, Antoni, Bolea Monte, Yolanda, Duan, Feng, Caiafa, Cesar F., Sun, Zhe, Sole Casals, Jordi   +9 more
core   +11 more sources

Daily Runoff Prediction Model Based on Multivariate Variational Mode Decomposition and Correlation Reconstruction [PDF]

长江科学院院报
[Objective] This study took Hanjiang River Basin as the study area. To better monitor the runoff conditions in Hanjiang River Basin, the daily runoff data collected from Ankang and Baihe hydroelectric power stations were selected for prediction analysis.
DING Jie, TU Peng-fei, FENG Yu, ZENG Huai-en
doaj   +2 more sources

Seismic Random Noise Denoising Using Mini-Batch Multivariate Variational Mode Decomposition. [PDF]

Comput Intell Neurosci, 2022
Seismic noise attenuation plays an important role in seismic interpretation. The empirical mode decomposition, synchrosqueezing wavelet transform, variational mode decomposition, etc., are often applied trace by trace. Multivariate empirical mode decomposition, multivariate synchrosqueezing wavelet transform, and multivariate variational mode ...
Wu G, Liu G, Wang J, Fan P.
europepmc   +4 more sources