A review of variational mode decomposition in seismic data analysis
Signal processing techniques play an important role in seismic data analysis. Variational
mode decomposition (VMD), as a powerful signal processing method, has been extensively …
mode decomposition (VMD), as a powerful signal processing method, has been extensively …
A comparative study of four kinds of adaptive decomposition algorithms and their applications
T Liu, Z Luo, J Huang, S Yan - Sensors, 2018 - mdpi.com
The adaptive decomposition algorithm is a powerful tool for signal analysis, because it can
decompose signals into several narrow-band components, which is advantageous to …
decompose signals into several narrow-band components, which is advantageous to …
Detection of epileptic seizures on EEG signals using ANFIS classifier, autoencoders and fuzzy entropies
A Shoeibi, N Ghassemi, M Khodatars… - … Signal Processing and …, 2022 - Elsevier
Epileptic seizures are one of the most crucial neurological disorders, and their early
diagnosis will help the clinicians to provide accurate treatment for the patients. The …
diagnosis will help the clinicians to provide accurate treatment for the patients. The …
Research on variational mode decomposition in rolling bearings fault diagnosis of the multistage centrifugal pump
M Zhang, Z Jiang, K Feng - Mechanical Systems and Signal Processing, 2017 - Elsevier
Rolling bearing faults are among the primary causes of breakdown in multistage centrifugal
pump. A novel method of rolling bearings fault diagnosis based on variational mode …
pump. A novel method of rolling bearings fault diagnosis based on variational mode …
Non-ferrous metals price forecasting based on variational mode decomposition and LSTM network
Y Liu, C Yang, K Huang, W Gui - Knowledge-Based Systems, 2020 - Elsevier
Non-ferrous metals are indispensable industrial materials and strategic supports of national
economic development. The price forecasting of non-ferrous metals is critical for investors …
economic development. The price forecasting of non-ferrous metals is critical for investors …
A hybrid stock price index forecasting model based on variational mode decomposition and LSTM network
H Niu, K Xu, W Wang - Applied Intelligence, 2020 - Springer
Abstract Changes in the composite stock price index are a barometer of social and
economic development. To improve the accuracy of stock price index prediction, this paper …
economic development. To improve the accuracy of stock price index prediction, this paper …
Successive variational mode decomposition
M Nazari, SM Sakhaei - Signal Processing, 2020 - Elsevier
Variational mode decomposition (VMD) is a powerful technique for concurrently
decomposing a signal into its constituent intrinsic modes. However, the performance of VMD …
decomposing a signal into its constituent intrinsic modes. However, the performance of VMD …
A VMD-EWT-LSTM-based multi-step prediction approach for shield tunneling machine cutterhead torque
G Shi, C Qin, J Tao, C Liu - Knowledge-Based Systems, 2021 - Elsevier
Cutterhead torque is an important operational parameter that reflects the obstruction degree
of geological environment to shield tunneling machine. Accurate multi-step prediction for …
of geological environment to shield tunneling machine. Accurate multi-step prediction for …
Fourier–Bessel series expansion based empirical wavelet transform for analysis of non-stationary signals
In this paper, a new method has been presented for the time–frequency (TF) representation
of non-stationary signals. The existing empirical wavelet transform (EWT) has been …
of non-stationary signals. The existing empirical wavelet transform (EWT) has been …
EEG Signal denoising using hybrid approach of Variational Mode Decomposition and wavelets for depression
Background Artifact contamination reduces the accuracy of various EEG based
neuroengineering applications. With time, biomedical signal denoising has been the utmost …
neuroengineering applications. With time, biomedical signal denoising has been the utmost …