Results 1 to 10 of about 34,434 (155)

A Source Localization Method Using Complex Variational Mode Decomposition [PDF]

Sensors, 2022
Source localization with a passive sensors array is a common topic in various areas. Among the popular source localization algorithms, the compressive sensing (CS)-based method has recently drawn considerable interest because it is a high-resolution ...
Qiuyan Miao, Xinglin Sun, Bin Wu, Lingyun Ye, Kaichen Song   +4 more
doaj   +4 more sources

A Modified Complex Variational Mode Decomposition Method for Analyzing Nonstationary Signals with the Low-Frequency Trend [PDF]

Sensors, 2022
Complex variational mode decomposition (CVMD) has been proposed to extend the original variational mode decomposition (VMD) algorithm to analyze complex-valued data.
Qiuyan Miao, Qingxin Shu, Bin Wu, Xinglin Sun, Kaichen Song   +4 more
doaj   +5 more sources

Adaptive Complex Variational Mode Decomposition for Micro-Motion Signal Processing Applications [PDF]

Sensors, 2021
In order to suppress the strong clutter component and separate the effective fretting component from narrow-band radar echo, a method based on complex variational mode decomposition (CVMD) is proposed in this paper.
Saiqiang Xia, Jun Yang, Wanyong Cai, Chaowei Zhang, Liangfa Hua, Zibo Zhou   +5 more
doaj   +5 more sources

Denoising Method for NV-Center Fluorescence Signals Based on MPA-VMD Combined with Wavelet Thresholding [PDF]

Micromachines
To address complex noise in nitrogen-vacancy center fluorescence signal acquisition, a hybrid denoising framework combining marine predators algorithm-optimized variational mode decomposition (VMD) and wavelet thresholding is proposed.
Yanxin He, Xin Li, Zhonghao Li, Hao Guo, Huan Fei Wen, Jun Tang, Jun Liu   +6 more
doaj   +2 more sources

A novel fault diagnosis method for gearbox based on RVMD and TELM with composite chaotic grey wolf optimizer [PDF]

Scientific Reports
Fault diagnosis for gearbox by robust variational mode decomposition (RVMD) and twin extreme learning machine (TELM) with composite chaotic grey wolf optimizer (CCGWO) is proposed in this study. Robust variational mode decomposition is an advanced signal
Xuebin Huang, Anfeng Xu, Hongbing Liu, Bingcheng Ye   +3 more
doaj   +2 more sources

Deep Prediction Model Based on Dual Decomposition with Entropy and Frequency Statistics for Nonstationary Time Series

Entropy, 2022
The prediction of time series is of great significance for rational planning and risk prevention. However, time series data in various natural and artificial systems are nonstationary and complex, which makes them difficult to predict.
Zhigang Shi, Yuting Bai, Xuebo Jin, Xiaoyi Wang, Tingli Su, Jianlei Kong   +5 more
doaj   +1 more source

Arrhythmia Classification Based on Adaptive Refined Composite Multiscale Fluctuation Dispersion Entropy [PDF]

International Journal Bioautomation, 2023
To improve the accuracy of electrocardiography (ECG) signal classification and identify abnormal heart rhythms, an arrhythmia classification algorithm based on adaptive refined composite multiscale fluctuation dispersion entropy (ARCMFDE) is proposed ...
Changsheng Zhang, Xin Ding, Changping Tian, Wei Peng   +3 more
doaj   +1 more source

A Novel Denoising Method for Ship-Radiated Noise

Journal of Marine Science and Engineering, 2023
Ship-radiated noise (SN) is one of the most critical signals in the complex marine environment; however, it is inevitably contaminated by the marine environment’s noise as well as noise from other equipment.
Yuxing Li, Chunli Zhang, Yuhan Zhou
doaj   +1 more source

Robust Estimation of Arrival Time of Complex Noisy Partial Discharge Pulse in Power Cables Based on Adaptive Variational Mode Decomposition [PDF]

Applied Sciences, 2020
Periodic narrowband signals and white noise are the main interferences in online detection and localization of cable partial discharge (PD), however, existing research has always focused on the white noise suppression only, which is not in line with the actual scene.
Sun, Wu, Li, Zhang
openaire   +2 more sources

Three-dimensional instantaneous orbit map for rotor-bearing system based on a novel multivariate complex variational mode decomposition algorithm

Mechanical Systems and Signal Processing, 2022
Full spectrum and holospectrum are homogenous information fusion technology developed for the fault diagnosis of rotating machinery, which is extensively exploited in the analysis of the orbits of rotor-bearing systems. However, they are not adapted for non-stationary signals, nor can they be used for fusion analysis of vibrations of multiple bearing ...
Xiaolong Cui, Jie Huang, Chaoshun Li, Yujie Zhao   +3 more
openaire   +2 more sources