Seizure detection from EEG signals using Multivariate Empirical Mode Decomposition [PDF]
Computers in Biology and Medicine, 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. MEMD is a multivariate extension of empirical mode decomposition (EMD), which is an established method to perform the decomposition and time-frequency (T-F) analysis of non-stationary ...
Zahra, Asmat +4 more
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Early Fault Detection Method for Rotating Machinery Based on Harmonic-Assisted Multivariate Empirical Mode Decomposition and Transfer Entropy [PDF]
Entropy, 2018 It is a difficult task to analyze the coupling characteristics of rotating machinery fault signals under the influence of complex and nonlinear interference signals.
Zhe Wu +4 more
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Multivariate empirical mode decomposition and application to multichannel filtering [PDF]
Signal Processing, 2011 Empirical Mode Decomposition (EMD) is an emerging topic in signal processing research, applied in various practical fields due in particular to its data-driven filter bank properties. In this paper, a novel EMD approach called X-EMD (eXtended-EMD) is proposed, which allows for a straightforward decomposition of mono- and multivariate signals without ...
Fleureau, Julien +4 more
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Multi-Fault Diagnosis of Rolling Bearings via Adaptive Projection Intrinsically Transformed Multivariate Empirical Mode Decomposition and High Order Singular Value Decomposition [PDF]
Sensors, 2018 Rolling bearings are important components in rotary machinery systems. In the field of multi-fault diagnosis of rolling bearings, the vibration signal collected from single channels tends to miss some fault characteristic information.
Rui Yuan, Yong Lv, Gangbing Song
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Measuring Center of Pressure Signals to Quantify Human Balance Using Multivariate Multiscale Entropy by Designing a Force Platform [PDF]
Sensors, 2013 To assess the improvement of human body balance, a low cost and portable measuring device of center of pressure (COP), known as center of pressure and complexity monitoring system (CPCMS), has been developed for data logging and analysis.
Cheng-Wei Huang +4 more
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Turning Tangent Empirical Mode Decomposition: A Framework for Mono- and Multivariate Signals [PDF]
IEEE Transactions on Signal Processing, 2011 A novel Empirical Mode Decomposition (EMD) algorithm, called 2T-EMD, for both mono- and multivariate signals is proposed in this paper. It differs from the other approaches by its computational lightness and its algorithmic simplicity. The method is essentially based on a redefinition of the signal mean envelope, computed thanks to new characteristic ...
Fleureau, Julien +4 more
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Multivariate Nonstationary Oscillation Simulation of Climate Indices With Empirical Mode Decomposition [PDF]
Water Resources Research, 2019 The objective of the current study is to build a stochastic model to simulate climate indices that are teleconnected with the hydrologic regimes of large‐scale water resources systems such as the Great Lakes system.
Taesam Lee, Taha B.M.J. Ouarda
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Weighted Window Sliding Multivariate Empirical Mode Decomposition for Online Multichannel Filtering
IEEE Access, 2018 Affected by nonlinear and non-stationary problems, classical linear analysis approaches may fail in analyzing real-world signals, such as the biomedical data.
Songbing Tao +3 more
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Adaptive-projection intrinsically transformed multivariate empirical mode decomposition in cooperative brain-computer interface applications. [PDF]
Philos Trans A Math Phys Eng Sci, 2016 Hemakom A +3 more
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Applied 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
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