Results 61 to 70 of about 4,786,449 (207)

Débruitage fréquentiel de signaux par EMD [PDF]

, 2013
Dans cet article, nous proposons un nouveau schéma de débruitage des signaux basé sur la décomposition modale empirique associée à une analyse fréquentielle.
DARE, Delphine, DARE-EMZIVAT, Delphine, BOUDRAA, Abdel-Ouahab, KOMATY, Ali   +3 more
core  

A Multi-Stage Decomposition and Hybrid Statistical Framework for Time Series Forecasting

Axioms
Modeling and forecasting nonstationary and nonlinear economic time series remain fundamentally challenging due to structural breaks, volatility clustering, and noise contamination that distort the intrinsic stochastic structure.
Swera Zeb Abbasi, Mahmoud M. Abdelwahab, Imam Hussain, Moiz Qureshi, Moeeba Rind, Paulo Canas Rodrigues, Ijaz Hussain, Mohamed A. Abdelkawy   +7 more
doaj   +1 more source

Multi‐Modal AI Approach in Depression Detection and Treatment: A Systematic Review of Last Decade

WIREs Data Mining and Knowledge Discovery, Volume 16, Issue 3, September 2026.
Overview of multimodal approaches for depression detection and treatment. ABSTRACT Depression is a common and devastating mental health illness with serious personal and societal consequences. Despite advancing treatment techniques, there are still hurdles in the effective diagnosis and treatment of depression, such as prompt diagnosis, personalized ...
Smith K. Khare, Esmaeil S. Nadimi, U. Rajendra Acharya, Victoria Blanes‐Vidal   +3 more
wiley   +1 more source

Rapid Magnetotail Reconfiguration and Ion‐Scale Wave Activity at Mercury

Journal of Geophysical Research: Space Physics, Volume 131, Issue 9, September 2026.
Abstract Mercury's magnetosphere is an extremely dynamic environment, where substorm‐like activity, including dipolarization fronts and particle acceleration, periodically disrupts the stability and radial extent of the closed field line region. The common narrowband ∼1 Hz waves at Mercury, near the local proton gyrofrequency are preferentially ...
M. Persson, R. M. Dewey, A. I. Eriksson, M. André, E. Yordanova, L. Richard, A. Dagore, J.‐E. Wahlund   +7 more
wiley   +1 more source

Multidecadal Changes in ENSO Drive a Substantial Decline in West Antarctic Sea Ice Predictability

Geophysical Research Letters, Volume 53, Issue 15, 16 August 2026.
Abstract ENSO teleconnections are a key source of Antarctic sea‐ice predictability, particularly in the Antarctic Dipole (ADP) region, but whether this predictability remains stable under the recent transition toward Central Pacific (CP) El Niño is unclear.
Yunhe Wang, Xiaojun Yuan, Xiaofeng Li, Yibin Ren, Bernard Wang   +4 more
wiley   +1 more source

Long‐Term Trends in the Ionospheric Equivalent Slab Thickness as a Proxy of Climate Change in the Ionosphere

Geophysical Research Letters, Volume 53, Issue 15, 16 August 2026.
Abstract Global warming warms the lower atmosphere, but cools and contracts the upper atmosphere. These changes also affect the ionosphere, altering the vertical distribution of plasma through changes in the plasma scale height. Here, we use ionospheric equivalent slab thickness (τ) multidecadal time series, derived through observations from co‐located
A. Pignalberi, T. Alberti
wiley   +1 more source

EMD Mode Mixing Separation of Signals with Close Spectral Proximity in Smart Grids [PDF]

, 2018
The Empirical Mode Decomposition (EMD) is a signal analysis method that separates multi-component signals into single oscillatory modes called intrinsic mode functions (IMFs).
Fosso, Olav B, Marta Molinas, Olav Bjarte Fosso, Molinas Cabrera, Maria Marta   +3 more
core   +1 more source

A Novel Source Number Enumeration Approach Based on Ensemble Learning and SEEMD

IEEE Access
Empirical Mode Decomposition (EMD) is a widely adopted adaptive signal analysis method, particularly effective for source number estimation in non-stationary environments. It decomposes complex signals into a series of Intrinsic Mode Functions (IMFs) and
Zhu Cairong, Ge Shengguo, Xu Yihan
doaj   +1 more source

Noncontact Measurement and Detection of Instantaneous Seismic Attributes Based on Complementary Ensemble Empirical Mode Decomposition

Energies, 2017
Hilbert–Huang transform (HHT) is a popular method to analyze nonlinear and non-stationary data. It has been widely used in geophysical prospecting. This paper analyzes the mode mixing problems of empirical mode decomposition (EMD) and introduces the ...
Yaping Huang, Haibin Di, Reza Malekian, Xuemei Qi, Zhixiong Li   +4 more
doaj   +1 more source

EMD Empirical Mode Decomposition

Empirical Mode Decomposition (EMD) is a data-driven method for analysing nonlinear and non-stationary signals. Through iterative sifting, it separates a signal into frequency-specific intrinsic mode functions and a residual trend. Combined with the Hilbert transform, EMD provides time-varying estimates of instantaneous amplitude and frequency ...
openaire   +3 more sources