Results 21 to 30 of about 640,363 (194)

Obtaining Information about Operation of Centrifugal Compressor from Pressure by Combining EEMD and IMFE

open access: yesEntropy, 2020
Based on entropy characteristics, some complex nonlinear dynamics of the dynamic pressure at the outlet of a centrifugal compressor are analyzed, as the centrifugal compressor operates in a stable and unstable state.
Yan Liu, Kai Ma, Hao He, Kuan Gao
doaj   +1 more source

Ground Roll Attenuation of Multicomponent Seismic Data with the Noise-Assisted Multivariate Empirical Mode Decomposition (NA-MEMD) Method

open access: yesApplied Sciences, 2022
Multicomponent seismic exploration provides more wavefield information for imaging complex subsurface structures and predicting reservoirs. Ground roll is strongly coherent noise in land multicomponent seismic data and exhibits similar features, which ...
Liying Xiao, Zhifu Zhang, Jianjun Gao
doaj   +1 more source

Gravitational waves in cosmological models of Ho\v{r}ava-Witten theory [PDF]

open access: yes, 2000
We study the behavior of gravitational waves and their backreaction on the background in cosmological solutions of the five-dimensional Ho\v{r}ava-Witten theory.
Kodama, Hideo, Seto, Osamu
core   +2 more sources

Time delay estimation based on variational mode decomposition

open access: yesAdvances in Mechanical Engineering, 2017
In order to improve the time delay estimation of colored noise signals, this article proposes generalized cross-correlation time delay estimation based on variational mode decomposition.
Jing-Yi Lu, Dong Ye, Wen-Ping Ma
doaj   +1 more source

Emotion Recognition Based On Electroencephalogram Signals Using Deep Learning Network

open access: yesJournal of Applied Science and Engineering, 2023
Deep learning networks have a high calculation volume, which is one of their problems. To solve this defect, the data of intrinsic modes obtained from the application of empirical mode decomposition to Electroencephalograph signals were used for the ...
Bin Wu
doaj   +1 more source

An adaptive denoising fault feature extraction method based on ensemble empirical mode decomposition and the correlation coefficient

open access: yesAdvances in Mechanical Engineering, 2017
Vibration signal processing is commonly used in the mechanical fault diagnosis. It contains abundant working status information. The vibration signal has some features such as non-linear and non-stationary. It has a lot of interference information. Fault
Huixiang Yang   +4 more
doaj   +1 more source

Instantaneous EEG Signal Analysis Based on Empirical Mode Decomposition Applied to Burst-Suppression in Propofol Anaesthesia

open access: yesОбщая реаниматология, 2021
The human electroencephalogram (EEG) constitutes a nonstationary, nonlinear electrophysiological signal resulting from synchronous firing of neurons in thalamocortical structures of the brain. Due to the complexity of the brain's physiological structures
G. Sobolova   +4 more
doaj   +1 more source

A Simple Mode on a Highly Excited Background: Collective Strength and Damping in the Continuum [PDF]

open access: yes, 1997
Simple states, such as isobaric analog states or giant resonances, embedded into continuum are typical for mesoscopic many-body quantum systems. Due to the coupling to compound states in the same energy range, a simple mode acquires a damping width ...
Sokolov, V. V., Zelevinsky, V. G.
core   +3 more sources

An orthogonal technique for empirical mode decomposition in Hilbert-Huang transform

open access: yesMATEC Web of Conferences, 2015
First, it is indicated that the intrinsic mode functions (IMF) obtained by the empirical mode decomposition (EMD) are not orthogonal. Then an orthogonal technique based on Gram-Schmidt method is proposed to obtain the complete orthogonal intrinsic mode ...
Lou Menglin, Huang Tianli
doaj   +1 more source

Turbulence Time Series Data Hole Filling using Karhunen-Loeve and ARIMA methods [PDF]

open access: yes, 2007
Measurements of optical turbulence time series data using unattended instruments over long time intervals inevitably lead to data drop-outs or degraded signals.
Beran J   +15 more
core   +2 more sources

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