Noise-Assisted Multivariate Empirical Mode Decomposition Based Emotion Recognition [PDF]
Electrica, 2018 Emotion state detection or emotion recognition cuts across different disciplines because of the many parameters that embrace the brain's complex neural structure, signal processing methods, and pattern recognition algorithms.
Pınar Özel +2 more
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Dynamically sampled multivariate empirical mode decomposition [PDF]
Electronics Letters, 2015 A method for accurate multivariate local mean estimation in the multivariate empirical mode decomposition algorithm by using a statistical data‐driven approach based on the Menger curvature measure and normal‐to‐anything variate‐generation method is proposed. This is achieved by aligning the projection vectors in the direction of the maximum ‘activity’
Rehman, N +4 more
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Ground Roll Attenuation of Multicomponent Seismic Data with the Noise-Assisted Multivariate Empirical Mode Decomposition (NA-MEMD) Method [PDF]
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
doaj +2 more sources
New achievements on daily reference evapotranspiration forecasting: Potential assessment of multivariate signal decomposition schemes [PDF]
Ecological Indicators, 2023 Reference evapotranspiration (ETo) is a vital climate parameter affecting plants' water use. ETo can generate large deficits in soil moisture and runoff in different regions and seasons, leading to uncertainties in drought warning systems.
Mumtaz Ali +8 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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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 ...
Asmat Zahra +4 more
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Deep Multi-Stage Reference Evapotranspiration Forecasting Model: Multivariate Empirical Mode Decomposition Integrated With the Boruta-Random Forest Algorithm [PDF]
IEEE Access, 2021 Evapotranspiration, as a combination of evaporation and transpiration of water vapour, is a primary component of global hydrological cycles. It accounts for significant loss of soil moisture from the earth to the atmosphere.
W. J. M. Lakmini Prarthana Jayasinghe +4 more
doaj +3 more sources
Adaptive noise suppression for low-S/N microseismic data based on ambient-noise-assisted multivariate empirical mode decomposition [PDF]
Frontiers in Physics, 2023 Microseismic monitoring data may be seriously contaminated by complex and nonstationary interference noises produced by mechanical vibration, which significantly impact the data quality and subsequent data-processing procedure.
Zhichao Yu +5 more
doaj +3 more sources
Plant-wide oscillation detection using multivariate empirical mode decomposition [PDF]
Computers & Chemical Engineering, 2018 Abstract Plant-wide oscillation detection is an important task in the maintenance of large-scale industrial control systems, owing to the fact that in an interactive multi-loop environment oscillation generated in one loop may propagate to the different parts of the plant.
Muhammad Faisal Aftab +2 more
core +6 more sources
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
doaj +3 more sources