Results 251 to 260 of about 5,207,763 (284)

BIDIMENSIONAL ENSEMBLE EMPIRICAL MODE DECOMPOSITION OF FUNCTIONAL BIOMEDICAL IMAGES

Advances in Adaptive Data Analysis, 2014
Positron emission tomography (PET) provides a functional imaging modality to detect signs of dementias in human brains. Two-dimensional empirical mode decomposition (2D EMD) provides means to analyze such images. It extracts characteristic textures from these images which may be fed into powerful classifiers trained to group these textures into ...
A. Neubauer, Ana Maria Tomé, Andreas Kodewitz, J. M. Górriz, Carlos García Puntonet, Elmar Wolfgang Lang   +5 more
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ASSESSING DISCONTINUOUS DATA USING ENSEMBLE EMPIRICAL MODE DECOMPOSITION

Advances in Adaptive Data Analysis, 2011
This investigation presents an improved ensemble empirical mode decomposition (EEMD) algorithm that can be applied to discontinuous data. The quality of the algorithm is assessed by creating artificial data gaps in continuous data, then comparing the extracted intrinsic mode functions (IMFs) from both data sets.
Bradley Lee Barnhart, Honda Kahindo Wa Nandage, William Eichinger   +2 more
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Ensemble Empirical Mode Decomposition for atherosclerosis in high-risk subjects

2011 8th International Conference on Information, Communications & Signal Processing, 2011
Photoplethysmography (PPG) is a popular non-invasive method of waveform contour analysis in assessing arterial stiffness. Although stiffness index (SI) is a good parameter in assessing atherosclerosis, it dose not perform in aged and arterial stiffness patients, because of their ill-defined diastolic peaks in digital volume pulse (DVP) waveforms.
Ching-Shuen Chen, Cyuan-Cin Liu, Hsien-Tsai Wu, An-Bang Liu   +3 more
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Purification of Axis Trace by Ensemble Empirical Mode Decomposition

Advanced Materials Research, 2013
Aiming at the purification of axis trace, a novel method was proposed by using ensemble empirical mode decomposition (EEMD). Ensemble empirical mode decomposition decomposed a complicated signal into a collection of intrinsic mode functions (IMFs). Then according to prior knowledge of rotating machinery, chose intrinsic mode function components and ...
Jia Xing Zhu, Wen Bin Zhang, Ya Song Pu, Yan Jie Zhou   +3 more
openaire   +1 more source

Ensemble Empirical Mode Decomposition for Machine Health Diagnosis

Key Engineering Materials, 2009
Ensemble Empirical Mode Decomposition (EEMD) is a new signal processing technique aimed at solving the problem of mode mixing present in the original Empirical Mode Decomposition (EMD) algorithm. This paper investigates its utility for machine health monitoring and defect diagnosis. The mechanism of EEMD is first introduced.
Jian Zhang, Ru Qiang Yan, Robert X. Gao
openaire   +1 more source

An Optimal Ensemble Empirical Mode Decomposition Method for Vibration Signal Decomposition

Journal of Vibration and Acoustics, 2017
The vibration signal decomposition is a critical step in the assessment of machine health condition. Though ensemble empirical mode decomposition (EEMD) method outperforms fast Fourier transform (FFT), wavelet transform, and empirical mode decomposition (EMD) on nonstationary signal decomposition, there exists a mode mixing problem if the two critical ...
Shi-Chang Du, Tao Liu, De-Lin Huang, Gui-Long Li   +3 more
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Rainfall Forecasting Based on Ensemble Empirical Mode Decomposition and Neural Networks

2013
480
Juan Beltrán-Castro, Juliana Valencia-Aguirre, Mauricio Orozco-Alzate, Germán Castellanos-Domínguez, Carlos Manuel Travieso-González   +4 more
openaire   +3 more sources

Classification of epileptic EEG data by using ensemble empirical mode decomposition

2018 26th Signal Processing and Communications Applications Conference (SIU), 2018
In this study, our aim is to distinguish pre-seizure and seizure data from epileptic EEG signals using Ensemble Empirical Mode Decomposition (EEMD) and various classifiers. For this purpose, epileptic EEG data from 13 epileptic patients have been recorded using surface electrodes at Izmir Kâtip Celebi University School of Medicine, Neurology Department.
Ozlem Karabiber Cura, Sibel Kocaaslan Atli, Reza Sadighzadeh, Aydin Akan   +3 more
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Quantitative diagnosis for bearing faults by improving ensemble empirical mode decomposition

ISA Transactions, 2018
In the bearing health assessment issues, using the adaptive nonstationary vibration signal processing methods in the time-frequency domain, lead to improving of early fault detection. On the other hand, the noise and random impulses which contaminates the input data, are a major challenge in extracting fault-related features.
Mohammad Sadegh, Hoseinzadeh, Siamak Esmaeilzadeh, Khadem, Mohammad Saleh, Sadooghi   +2 more
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A fast entropy assisted complete ensemble empirical mode decomposition algorithm

The 2014 2nd International Conference on Systems and Informatics (ICSAI 2014), 2014
Empirical mode decomposition (EMD) is a simple and real-time procedure to adaptively decompose a signal into a set of oscillation scales, but it faces the serious problem of mode mixing. The improved complete ensemble EMD with adaptive noise (Improved CEEMDAN) can successfully eliminate the mode mixing by adding white noise's IMFs and utilizing an ...
Yihai Liu, Xiaomin Zhang, Yang Yu 0040
openaire   +2 more sources