Results 261 to 270 of about 5,207,763 (284)

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
openaire   +2 more sources

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

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
openaire   +2 more sources

Improvement of the Ensemble Empirical Mode Decomposition with Parallel Computing

2019 Ural Symposium on Biomedical Engineering, Radioelectronics and Information Technology (USBEREIT), 2019
In this paper we propose a novel approach to increase a processing speed of the Ensemble Empirical Mode Decomposition algorithm and its Complementary version with usage of parallel computations. It is shown that this computational scheme is effective and leads to a significant increase in processing speed up to approximately 4.1 times with 8 parallel ...
openaire   +1 more source

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

GPGPU-Aided Ensemble Empirical-Mode Decomposition for EEG Analysis During Anesthesia

IEEE Transactions on Information Technology in Biomedicine, 2010
Ensemble empirical-mode decomposition (EEMD) is a novel adaptive time-frequency analysis method, which is particularly suitable for extracting useful information from noisy nonlinear or nonstationary data. Unfortunately, since the EEMD is highly compute-intensive, the method does not apply in real-time applications on top of commercial-off-the-shelf ...
Dan Chen 0001, Duan Li 0001, Muzhou Xiong, Hong Bao, Xiaoli Li 0002   +4 more
openaire   +3 more sources

Ensemble empirical mode decomposition based ECG noise filtering method

2010 International Conference on Machine Learning and Cybernetics, 2010
Electrocardiogram is often corrupted by various noises, such as high-frequency muscle contraction. In this study, ensemble empirical mode decomposition (EEMD) was used for ECG noise reduction. Gaussian noise was applied and the average (ensemble) intrinsic mode function (IMF) was used for ECG reconstruction.
openaire   +1 more source

Ensemble empirical mode decomposition for high frequency ECG noise reduction

Biomedizinische Technik/Biomedical Engineering, 2010
An electrocardiogram (ECG) is measured from the body surface and is often corrupted by various noises, such as high-frequency muscle contraction. Recently, empirical mode decomposition (EMD), a well-known analysis technique for nonlinear and non-stationary signals, has been employed for the purpose of ECG noise reduction. In this study, a modified EMD,
openaire   +2 more sources

Fault Feature Extraction of Gearboxes Using Ensemble Empirical Mode Decomposition

2011
The paper employs ensemble empirical mode decomposition (EEMD) to extract the fault information from the signal collected from a defective gearbox. In view of the shortcoming of the mode mixing which empirical mode decomposition (EMD) fails to overcome, the EEMD method is used to decompose the signal captured from the defective gearbox and successfully
openaire   +1 more source

Hardware architecture design for complementary ensemble empirical mode decomposition algorithm

Integration, 2023
Kaushik Das, Sambhu Nath Pradhan
openaire   +1 more source