Deep LSTM Surrogates for MEMD: A Noise-Assisted Approach to EEG Intrinsic Mode Function Extraction
InformationIn this paper, we propose a deep learning-based surrogate model for Multivariate Empirical Mode Decomposition (MEMD) using Long Short-Term Memory (LSTM) networks, aimed at efficiently extracting Intrinsic Mode Functions (IMFs) from ...
Pablo Andres Muñoz-Gutierrez +2 more
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Analysis of Weak Fault in Hydraulic System Based on Multi-scale Permutation Entropy of Fault-Sensitive Intrinsic Mode Function and Deep Belief Network. [PDF]
Entropy (Basel), 2019 With the aim of automatic recognition of weak faults in hydraulic systems, this paper proposes an identification method based on multi-scale permutation entropy feature extraction of fault-sensitive intrinsic mode function (IMF) and deep belief network ...
Huang J, Wang X, Wang D, Wang Z, Hua X.
europepmc +2 more sources
Mental Task Classification Scheme Utilizing Correlation Coefficient Extracted from Interchannel Intrinsic Mode Function. [PDF]
Biomed Res Int, 2017 In view of recent increase of brain computer interface (BCI) based applications, the importance of efficient classification of various mental tasks has increased prodigiously nowadays.
Rahman MM, Rahman MM, Fattah SA.
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Sensors, 2022 In order to study the characteristics of pressure fluctuation during unstable combustion, experimental studies had been conducted on the mechanism model of the swirl combustor and the industrial swirl combustor.
Xuhuai Wang +4 more
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Qualitative assessment of intrinsic mode functions of empirical mode decomposition [PDF]
2008 IEEE International Conference on Acoustics, Speech and Signal Processing, 2008 The 'empirical mode decomposition' (EMD) method has been recently proposed to deal with nonlinear and non- stationary data, which decomposes signals into 'well-behaved' intrinsic mode functions (IMFs). An assessment on the qualitative performance of the EMD method in terms of the degree of signal nature preservation of individual IMF is provided.
Mo Chen 0006 +3 more
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Analysis and Prediction of Cloud VM CPU Load Based on EMPC-BCGRU [PDF]
Jisuanji kexue, 2023 Cloud platform resource prediction is of great significance for resource management and energy saving.Cloud VM technology is a virtualization method implemented by the cloud to make full use of physical resources,but effective cloud VM load prediction is
XIE Tonglei, DENG Li, YOU Wenlong, LI Ruilong
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A New Intrinsic Mode Function Selection Method Based on Power Spectral Density
, 2021 Emprical Mode Decomposition is one of the mostly used decomposition method to decompose non-linear and non stationary multivariate signals into linear and stationary sub signals.
Kotan, Soner, AKAN, AYDIN
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Fault identification in pipeline system using normalized hilbert huang transform and automatic selection of intrinsic mode function [PDF]
, 2018 Pressure transient analysis have been widely studied for monitoring of pipeline healthy and condition assessment in water distribution systems. This technique has potential low cost, non intrusive nature and able to locate any uncertainties (leak, pipe ...
M. F., Ghazali +3 more
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Frontiers in Neuroscience, 2019 Resting-state functional connectivity MRI (rs-fcMRI) is a common method for mapping functional brain networks. However, estimation of these networks is affected by the presence of a common global systemic noise, or global signal (GS).
Narges Moradi +7 more
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De-noising method of mine gas monitoring data
Gong-kuang zidonghua, 2018 In order to solve problem of easily eliminating effective signal component of mine gas monitoring data by wavelet de-noising, a de-noising method of mine gas monitoring data based on Hilbert-Huang transform was proposed.
LIANG Rong, DONG Dingwen
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