Results 21 to 30 of about 196,483 (296)
Variational Mode Decomposition for Raman Spectral Denoising
Molecules, 2023 As a fast and non-destructive spectroscopic analysis technique, Raman spectroscopy has been widely applied in chemistry. However, noise is usually unavoidable in Raman spectra. Hence, denoising is an important step before Raman spectral analysis. A novel
Xihui Bian +4 more
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Turbulence Time Series Data Hole Filling using Karhunen-Loeve and ARIMA methods [PDF]
, 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
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International Journal of Distributed Sensor Networks, 2018 The bidimensional empirical mode decomposition algorithm is more suitable to handle image fusion than the traditional multi-scale decomposition methods in the image fusion area.
Pei Wang, Hui Fu, Ke Zhang
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Research of partial discharge detection for XLPE cable
Gong-kuang zidonghua, 2014 In order to extract characteristics of partial discharge signals, the paper proposed an adaptive threshold algorithm for processing partial discharge data by using ensemble empirical mode decomposition method for analysis of XLPE cable partial discharge ...
TANG Zhongyu +3 more
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Analysis of Vehicle Platform Vibration Based on Empirical Mode Decomposition
Shock and Vibration, 2021 Vehicle platform vibration (VPV) directly affects the measurement accuracy of precise measuring instrument (PMI) fixed on it. In order to reduce the influences of VPV on measurement accuracy, it is necessary to perform vibration isolation between vehicle
Chengwu Shen +5 more
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IEEE Access, 2017 Effective signal processing methods are essential for machinery fault diagnosis. Most conventional signal processing methods lack adaptability, thus being unable to well extract the embedded meaningful information.
Zhipeng Feng, Dong Zhang, Ming J. Zuo
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Seizure detection from EEG signals using Multivariate Empirical Mode Decomposition [PDF]
, 2017 We present a data driven approach to classify ictal (epileptic seizure) and non-ictal EEG signals using the multivariate empirical mode decomposition (MEMD) algorithm.
Ehsan, Shoaib +4 more
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Empirical mode decomposition with shape-preserving spline interpolation
Results in Applied Mathematics, 2020 Empirical mode decomposition (EMD) is a popular, novel, user-friendly algorithm to decompose a given signal into its constituting components, utilizing spline interpolation.
Maria D. van der Walt
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Empirical Mode Decomposition Based Multi-Modal Activity Recognition
Sensors, 2020 This paper aims to develop an activity recognition algorithm to allow parents to monitor their children at home after school. A common method used to analyze electroencephalograms is to use infinite impulse response filters to decompose the ...
Lingyue Hu +4 more
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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 +2 more
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