Results 21 to 30 of about 338,685 (349)

Objective Empirical Mode Decomposition metric

International Journal of Advances in Telecommunications, Electrotechnics, Signals and Systems, 2016
Empirical Mode Decomposition (EMD) is a data-driven technique for extraction of oscillatory components from data. Although it has been introduced over 15 years ago, its mathematical foundations are still missing which also implies lack of objective ...
Dawid Laszuk, Oswaldo Jose Cadenas, Sławomir Jarosław Nasuto   +2 more
doaj   +1 more source

Empirical mode decomposition-based facial pose estimation inside video sequences [PDF]

, 2010
We describe a new pose-estimation algorithm via integration of the strength in both empirical mode decomposition (EMD) and mutual information. While mutual information is exploited to measure the similarity between facial images to estimate poses, EMD is
Jiang, Jianmin, Qing, Chunmei, Yang, Zhijing   +2 more
core   +1 more source

Fast Multivariate Empirical Mode Decomposition

IEEE Access, 2018
The multivariate empirical mode decomposition (MEMD) has been pioneered recently for adaptively processing of multichannel data. Despite its high efficiency on time-frequency analysis of nonlinear and nonstationary signals, high computational load and ...
Xun Lang, Qian Zheng, Zhiming Zhang, Shan Lu, Lei Xie, Alexander Horch, Hongye Su   +6 more
doaj   +1 more source

Weak Signal Enhance Based on the Neural Network Assisted Empirical Mode Decomposition

Sensors, 2020
In order to enhance weak signals in strong noise background, a weak signal enhancement method based on EMDNN (neural network-assisted empirical mode decomposition) is proposed.
Kai Chen, Kai Xie, Chang Wen, Xin-Gong Tang   +3 more
doaj   +1 more source

A Novel Decomposition-Ensemble Learning Model Based on Ensemble Empirical Mode Decomposition and Recurrent Neural Network for Landslide Displacement Prediction

Applied Sciences, 2021
As vital comments on landslide early warning systems, accurate and reliable displacement prediction is essential and of significant importance for landslide mitigation.
Xiaoxu Niu, Junwei Ma, Yankun Wang, Junrong Zhang, Hongjie Chen, Huiming Tang   +5 more
semanticscholar   +1 more source

Composite fault diagnosis of gearbox based on empirical mode decomposition and improved variational mode decomposition

Journal of Low Frequency Noise, Vibration and Active Control, 2021
In order to identify the nonlinear nonstationary pitting-wear fault signal of gears in gearbox, a new method of composite fault diagnosis for gearbox is proposed, which combines empirical mode decomposition with improved variational mode decomposition ...
Jingyue Wang, Jiangang Li, Haotian Wang, Lixin Guo   +3 more
doaj   +1 more source

Analysis of Functional Brain Network in MDD Based on Improved Empirical Mode Decomposition With Resting State EEG Data

IEEE transactions on neural systems and rehabilitation engineering, 2021
At present, most brain functional studies are based on traditional frequency bands to explore the abnormal functional connections and topological organization of patients with depression.
Xuexiao Shao, Shuting Sun, Jianxiu Li, Wenwen Kong, Jing Zhu, Xiaowei Li, Bin Hu   +6 more
semanticscholar   +1 more source

A pixel-level entropy-weighted image fusion algorithm based on bidimensional ensemble empirical mode decomposition

International Journal of Distributed Sensor Networks, 2018
The bidimensional empirical mode decomposition algorithm is more suitable to handle image fusion than the traditional multi-scale decomposition methods in the image fusion area.
Pei Wang, Hui Fu, Ke Zhang
doaj   +1 more source

Research of partial discharge detection for XLPE cable

Gong-kuang zidonghua, 2014
In order to extract characteristics of partial discharge signals, the paper proposed an adaptive threshold algorithm for processing partial discharge data by using ensemble empirical mode decomposition method for analysis of XLPE cable partial discharge ...
TANG Zhongyu, CHU Xin, HAN Gang, YU Yuese   +3 more
doaj   +1 more source

Variational Mode Decomposition for Raman Spectral Denoising

Molecules, 2023
As a fast and non-destructive spectroscopic analysis technique, Raman spectroscopy has been widely applied in chemistry. However, noise is usually unavoidable in Raman spectra. Hence, denoising is an important step before Raman spectral analysis. A novel
Xihui Bian, Zitong Shi, Yingjie Shao, Yuanyuan Chu, Xiaoyao Tan   +4 more
doaj   +1 more source