Results 31 to 40 of about 31,823 (308)
Enhancing Performance of Single-Channel SSVEP-Based Visual Acuity Assessment via Mode Decomposition
IEEE Transactions on Neural Systems and Rehabilitation Engineering, 2023 This study aimed to improve the performance of single-channel steady-state visual evoked potential (SSVEP)-based visual acuity assessment by mode decomposition methods.
Xiaowei Zheng +3 more
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, 2013 In this paper a new adaptive audio watermarking algorithm based on Empirical Mode Decomposition (EMD) is introduced. The audio signal is divided into frames and each one is decomposed adaptively, by EMD, into intrinsic oscillatory components called ...
KHALDI, Kais, BOUDRAA, Abdel-Ouahab
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A comparative study of single-channel signal processing methods in fetal phonocardiography.
PLoS ONE, 2022 Fetal phonocardiography is a non-invasive, completely passive and low-cost method based on sensing acoustic signals from the maternal abdomen. However, different types of interference are sensed along with the desired fetal phonocardiography.
Katerina Barnova +4 more
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Empirical Mode Decomposition Aided by Adaptive Low Pass Filtering [PDF]
, 2012 Empirical Mode Decomposition (EMD) is an adaptive signal analysis technique which derives its basis functions from the signal itself. EMD is realized through successive iterations of a sifting process requiring local mean computation.
Arıkan, Orhan +6 more
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on the Influence of Sampling on the Empirical Mode Decomposition [PDF]
2006 IEEE International Conference on Acoustics Speed and Signal Processing Proceedings, 2006 The rationale underlying the nonlinear Empirical Mode Decomposition method is intrinsically a continuous-time approach. The method can however only be applied in practice to discrete-time signals. EMD is obtained through iterating a basic nonlinear operator for which we derive an upper bound for the effects of sampling.
Gabriel Rilling, Patrick Flandrin
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Weak Signal Enhance Based on the Neural Network Assisted Empirical Mode Decomposition
Sensors, 2020 In order to enhance weak signals in strong noise background, a weak signal enhancement method based on EMDNN (neural network-assisted empirical mode decomposition) is proposed.
Kai Chen +3 more
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Journal of Low Frequency Noise, Vibration and Active Control, 2021 In order to identify the nonlinear nonstationary pitting-wear fault signal of gears in gearbox, a new method of composite fault diagnosis for gearbox is proposed, which combines empirical mode decomposition with improved variational mode decomposition ...
Jingyue Wang +3 more
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SAMPLING EFFECTS ON THE EMPIRICAL MODE DECOMPOSITION [PDF]
Advances in Adaptive Data Analysis, 2009 Standard exposition of Empirical Mode Decomposition (EMD) is usually done within a continuous-time setting whereas, in practice, the effective implementation always operates in discrete-time. The purpose of this contribution is to summarize a number of results aimed at quantifying the influence of sampling on EMD.
Gabriel Rilling, Patrick Flandrin
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Thermal Image Enhancement using Bi-dimensional Empirical Mode Decomposition in Combination with Relevance Vector Machine for Rotating Machinery Fault Diagnosis [PDF]
, 2009 In this study, a novel fault diagnosis system for rotating machinery using thermal imaging is proposed. This system consists of bi-dimensional empirical mode decomposition (BEMD) for image enhancement, a generalized discriminant analysis (GDA) for ...
Yang, Bo-Suk +7 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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