Results 31 to 40 of about 640,363 (194)

Hierarchical-Variational Mode Decomposition for Baseline Correction in Electroencephalogram Signals

IEEE Open Journal of Instrumentation and Measurement, 2023
Electroencephalogram (EEG) signals being time-resolving signals, suffer very often from baseline drift caused by eye movements, breathing, variations in differential electrode impedances, movement of the subject, and so on.
Shireen Fathima, Maaz Ahmed
doaj   +1 more source

Lagrangian single particle turbulent statistics through the Hilbert-Huang Transform [PDF]

, 2012
The Hilbert-Huang transform is applied to analyze single particle Lagrangian velocity data from numerical simulations of hydrodynamic turbulence. The velocity trajectory is described in terms of a set of intrinsic mode functions, C_{i}(t), and of their ...
Biferale, Luca, Calzavarini, Enrico, Huang, Yongxiang, Sun, Chao, Toschi, Federico   +4 more
core   +8 more sources

Application of Adaptive Local Iterative Filtering and Fuzzy Entropy in Gear Fault Identification

Jixie chuandong, 2021
Aiming at the problem that the measured signal of gear system can’t accurately reflect the fault characteristics due to noise interference， a fault identification method combining adaptive local iterative filtering and fuzzy entropy is proposed. By using
Wenbin Zhang, Jie Jiang, Yasong Pu, Libin Yu, Dewei Guo, Jie Min   +5 more
doaj  

Brief Communication: Earthquake sequencing: analysis of time series constructed from the Markov chain model [PDF]

Nonlinear Processes in Geophysics, 2015
Directed graph representation of a Markov chain model to study global earthquake sequencing leads to a time series of state-to-state transition probabilities that includes the spatio-temporally linked recurrent events in the record-breaking sense.
M. S. Cavers, K. Vasudevan
doaj   +1 more source

Empirical Mode Decomposition-Derived Entropy Features Are Beneficial to Distinguish Elderly People with a Falling History on a Force Plate Signal

Entropy, 2021
Fall risk prediction is an important issue for the elderly. A center of pressure signal, derived from a force plate, is useful for the estimation of body calibration.
Li-Wei Chou, Kang-Ming Chang, Yi-Chun Wei, Mei-Kuei Lu   +3 more
doaj   +1 more source

Orthogonal intrinsic mode functions via optimization approach

Journal of Industrial & Management Optimization, 2021
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Wang, Xinpeng, Ling, Bingo Wing-Kuen, Kuang, Wei-Chao, Yang, Zhijing   +3 more
openaire   +3 more sources

Very Short-Term Wind Direction Multistep Forecast Based on VMD-LSTM

南方能源建设, 2023
[Introduction] In order to accurately forecast the wind direction in the next 4 hours, a very short-term wind direction multistep forecast algorithm based on VMD-LSTM（Variational Mode Decomposition-Long Short-Term Memory） is proposed.
Xiuhao LI, Huaixi LIU, Zhiyong ZHANG, Min ZHANG, Di WU, Desheng MIAO   +5 more
doaj   +1 more source

Order parameter fluctuations in the holographic superconductor

, 2017
We investigate the effect of order parameter fluctuations in the holographic superconductor. In particular, using a fully backreacted bulk geometry, the intrinsic spectral functions of the order parameter in both the normal and the superconducting phase ...
Plantz, N. W. M., Stoof, H. T. C., Vandoren, S.   +2 more
core   +1 more source

Hybrid short-term traffic flow prediction model of intersections based on improved complete ensemble empirical mode decomposition with adaptive noise

Advances in Mechanical Engineering, 2019
Based on improved complete ensemble empirical mode decomposition with adaptive noise (ICEEMDAN) algorithm and kernel online sequential extreme learning machine (KOSELM) algorithm, a new hybrid short-term traffic flow prediction model (ICEEMDAN-KOSELM ...
Xiujuan Tian, Dexin Yu, Xue Xing, Shiguang Wang, Zhuorui Wang   +4 more
doaj   +1 more source

Kernel recursive least square tracker and long-short term memory ensemble based battery health prognostic model

iScience, 2021
Summary: A data-driven approach is developed to predict the future capacity of lithium-ion batteries (LIBs) in this work. The empirical mode decomposition (EMD), kernel recursive least square tracker (KRLST), and long short-term memory (LSTM) are used to
Muhammad Umair Ali, Karam Dad Kallu, Haris Masood, Kamran Ali Khan Niazi, Muhammad Junaid Alvi, Usman Ghafoor, Amad Zafar   +6 more
doaj   +1 more source