Results 181 to 190 of about 1,862 (208)

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   +2 more sources

Mining anomalous electricity consumption using Ensemble Empirical Mode Decomposition

2013 IEEE International Conference on Acoustics, Speech and Signal Processing, 2013
Sensor deployments in large buildings allow the administrators to supervise the building infrastructure and identify abnormalities. Nevertheless, the numerous data streams reported by the increasing number of sensors overwhelm the building administrators. We propose a methodology that assists them to identify abnormal devices usages.
Romain Fontugne, Nicolas Tremblay, Pierre Borgnat, Patrick Flandrin, Hiroshi Esaki   +4 more
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Ensemble empirical mode decomposition based feature enhancement of cardio signals

Medical Engineering & Physics, 2012
This paper presents an application of ensemble empirical mode decomposition method for enhancement of specific biological signal features. The application for two types of cardiological signals is presented in this article. Detection of fiducial points is a routine task for analyzing these signals.
Artūras, Janušauskas, Vaidotas, Marozas, Arūnas, Lukoševičius   +2 more
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Cardiogenic oscillations extraction in inductive plethysmography: Ensemble empirical mode decomposition

2009 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2009
The purpose of this study is to investigate the potential of the ensemble empirical mode decomposition (EEMD) to extract cardiogenic oscillations from inductive plethysmography signals in order to measure cardiac stroke volume. First, a simple cardio-respiratory model is used to simulate cardiac, respiratory, and cardio-respiratory signals.
Abdulhay, Enas, Guméry, Pierre-Yves, Fontecave Jallon, Julie, Baconnier, Pierre   +3 more
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Ensemble Empirical Mode Decomposition and adaptive filtering for ECG signal enhancement

2012 IEEE International Symposium on Medical Measurements and Applications Proceedings, 2012
The morphologic analysis of electrocardiogram (ECG) signals, which are always contaminated by certain types of noise, is a very important standard for medical diagnosis of heart diseases and other pathological phenomena. In this paper a novel ECG enhancement method based on Ensemble Empirical Mode Decomposition (EEMD) and adaptive filtering is proposed
Xiaochuan He, Rafik A. Goubran, Xiaoping P. Liu   +2 more
openaire   +1 more source

GPU-based Ensemble Empirical Mode Decomposition approach to spectrum discrimination

2012 4th Workshop on Hyperspectral Image and Signal Processing (WHISPERS), 2012
Because of the improvement of optical remote sensing instrument, hyperspectral images now collect information of the ground with hundreds of wavelengths. This spectral information can be used to identify different materials, since each material should have its unique absorption spectrum.
Yung-Ling Wang, Hsuan Ren, Min-Yu Huang, Yang-Lang Chang   +3 more
openaire   +1 more source

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   +1 more source

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
openaire   +1 more source