Results 41 to 50 of about 18,123 (142)
Schrausser/SCR-EMD: Windows screensaver simulating EMD treatment
, 2023 Microsoft Windows screensaver simulating ...
Schrausser, Dietmar
core +1 more source
Optimized Fast Learning Network for Groundwater Level Prediction Based on Several Data Decomposition Techniques [PDF]
长江科学院院报[Objective] To improve the accuracy of groundwater level time series prediction and explore the application effects of 17 decomposition techniques—EMD, EEMD, CEEMD, ICEEMD, LMD, RLMD, ITD, ESMD, WT, WPT, EWT, VMD, SSA, TVF-EMD, FDM, SGMD, and SVMD—in the
PAN Xiu-chang, PAN Si-cheng, CUI Dong-wen
doaj +1 more source
Applied SciencesTo tackle the low signal-to-noise ratio (SNR) of surface electromyography (sEMG) signals during upper-limb rehabilitation training—an issue arising from noise interference that undermines downstream motion recognition—this work develops a novel denoising
Xuewang Song +3 more
doaj +1 more source
tvf-EMD based time series analysis of $^{7}$Be of the CTBTO-IMS network
, 2018 A methodology of adaptive time series analysis based on Empirical Mode Decomposition (EMD) has been employed to investigate $^{7}$Be activity concentration variability, along with temperature. Analysed data were sampled at ground level by 28 different stations of the CTBTO-IMS network.
Longo, Alessandro +2 more
openaire +2 more sources
Photovoltaic Power Forecasting: A Review on Models and Future Research Directions
IET Renewable Power Generation, Volume 20, Issue 1, January/December 2026.It provides a detailed review of PV power forecasting for the AI‐models and future research directions. ABSTRACT The stability of power grid systems can be significantly affected by the unpredictability and volatility of power generation; however, accurate forecasting of solar energy power can help reduce this impact.
Upma Singh +3 more
wiley +1 more source
Drought stands as a highly perilous natural catastrophe that impacts numerous facets of human existence. Drought data is nonstationary and noisy, posing challenges for accurate forecasting. This study proposes a novel hybrid framework integrating TVF-EMD
Yaseen, Zaher Mundher +6 more
core +2 more sources
, 2016 This paper presents a novel method for feature extraction from electroencephalogram (EEG) signals using empirical mode decomposition (EMD). Its use is motivated by the fact that the EMD gives an effective time-frequency analysis of nonstationary signals.
Ali Hassan (836158) +4 more
core +5 more sources
Explainable Optimized LSTM Model for Sustainable Wind Power Forecasting in Smart Cities
International Journal of Intelligent Systems, Volume 2026, Issue 1, 2026.Accurate wind‐power forecasting is essential for the successful integration of renewable energy into smart city grids. Traditional long short‐term memory (LSTM) networks face significant challenges in parameter optimization, leading to suboptimal forecasting performance.
Abdulaziz Shehab +4 more
wiley +1 more source
Wavelet‐based fundamental heart sound recognition method using morphological and interval features
Healthcare Technology Letters, Volume 5, Issue 3, Page 81-87, June 2018., 2018 Accurate and reliable recognition of fundamental heart sounds (FHSs) plays a significant role in automated analysis of heart sound (HS) patterns. This Letter presents an automated wavelet‐based FHS recognition (WFHSR) method using morphological and interval features.
V. Nivitha Varghees +2 more
wiley +1 more source
Purification of Low‐Complexity Domain Proteins FUS, EWSR1, and Their Fusions
Current Protocols, Volume 5, Issue 4, April 2025.Abstract FET proteins are large multifunctional proteins that have several key roles in biology. The FET family of proteins, including FUS, EWSR1, and TAF15, play critical roles in transcription regulation, RNA processing, and DNA damage repair.
Jesse J. Altemus +3 more
wiley +1 more source