Results 41 to 50 of about 338,685 (349)

WAVELET TRANSFORMS FOR EEG SIGNAL DENOISING AND DECOMPOSITION

International Journal of Advances in Signal and Image Sciences, 2023
EEG signal analysis is difficult because there are so many unwanted impulses from non-cerebral sources. Presently, methods for eliminating noise through selective frequency filtering are afflicted with a notable deprivation of EEG information. Therefore,
Ibtihal Hassan Elshekhidris, Magdi Baker MohamedAmien, Ahmed Fragoon   +2 more
doaj   +1 more source

Soil Temperature Prediction Using Convolutional Neural Network Based on Ensemble Empirical Mode Decomposition

IEEE Access, 2021
Soil temperature plays an important role in agriculture, industry and other fields. Accurate soil temperature prediction can help improve productivity and avoid risks in many fields.
Huibowen Hao, Fanhua Yu, Qingliang Li
semanticscholar   +1 more source

Depth of anesthesia prediction via EEG signals using convolutional neural network and ensemble empirical mode decomposition

Mathematical Biosciences and Engineering, 2021
According to a recently conducted survey on surgical complication mortality rate, 47% of such cases are due to anesthetics overdose. This indicates that there is an urgent need to moderate the level of anesthesia. Recently deep learning (DL) methods have
Ravichandra Madanu, Farhan Rahman, Maysam F. Abbod , Shou-Zen Fan, Jiann-Shing Shieh   +4 more
doaj   +1 more source

Empirical mode decomposition with missing values [PDF]

, 2016
This paper considers an improvement of empirical mode decomposition (EMD) in the presence of missing data. EMD has been widely used to decompose nonlinear and nonstationary signals into some components according to intrinsic frequency called intrinsic ...
Donghoh Kim, Hee-Seok Oh
core   +1 more source

Automatic Interference Term Retrieval From Spectral Domain Low-Coherence Interferometry Using the EEMD-EMD-Based Method

IEEE Photonics Journal, 2016
Low-coherence interferometry (LCI) has proved to be a useful tool in optical measurement and detection. However, the noise that is present in practical applications makes interference term retrieval (ITR) difficult.
Hongxia Zhang, Feng Wang, Dagong Jia, Tiegen Liu, Yimo Zhang   +4 more
doaj   +1 more source

Tatouage audio par EMD [PDF]

, 2013
In this paper a new adaptive audio watermarking algorithm based on Empirical Mode Decomposition (EMD) is introduced. The audio signal is divided into frames and each one is decomposed adaptively, by EMD, into intrinsic oscillatory components called ...
BOUDRAA, Abdel-Ouahab, KHALDI, Kais
core   +5 more sources

New insights and best practices for the successful use of Empirical Mode Decomposition, Iterative Filtering and derived algorithms

Scientific Reports, 2020
Algorithms based on Empirical Mode Decomposition (EMD) and Iterative Filtering (IF) are largely implemented for representing a signal as superposition of simpler well-behaved components called Intrinsic Mode Functions (IMFs).
Angela Stallone, A. Cicone, M. Materassi
semanticscholar   +1 more source

Codage des signaux par EMD [PDF]

, 2012
In this letter a new signals coding framework based on the Empirical Mode Decomposition (EMD) is introduced. The EMD breaks down any signal into a reduced number of oscillating components called Intrinsic Modes Decomposition (IMFs).
BOUDRAA, Abdel-Ouahab, KHALDI, Kais
core   +4 more sources

Screening of Obstructive Sleep Apnea with Empirical Mode Decomposition of Pulse Oximetry

, 2014
Detection of desaturations on the pulse oximetry signal is of great importance for the diagnosis of sleep apneas. Using the counting of desaturations, an index can be built to help in the diagnosis of severe cases of obstructive sleep apnea-hypopnea ...
Di Persia, Leandro E., Larrateguy, Luis D., Milone, Diego H., Schlotthauer, Gastón   +3 more
core   +1 more source

Clustering Algorithm Reveals Dopamine‐Motor Mismatch in Cognitively Preserved Parkinson's Disease

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective To explore the relationship between dopaminergic denervation and motor impairment in two de novo Parkinson's disease (PD) cohorts. Methods n = 249 PD patients from Parkinson's Progression Markers Initiative (PPMI) and n = 84 from an external clinical cohort.
Rachele Malito, Chiara Meneghini, Alice Galli, Luca Gallo, Pierfrancesco Mitrotti, Paola Dimartino, Marianna Inglese, Cinzia Zatti, Alessandro Lupini, Andrea Pilotto, Alessandro Padovani, Micol Avenali, Enza Maria Valente, Cristina Tassorelli, Silvia P. Caminiti   +14 more
wiley   +1 more source