Results 41 to 50 of about 44,498 (172)
A Complex Empirical Mode Decomposition for Multivariant Traffic Time Series
Electronics, 2023 Data-driven modeling methods have been widely used in many applications or studies of traffic systems with complexity and chaos. The empirical mode decomposition (EMD) family provides a lightweight analytical method for non-stationary and non-linear data.
Guochen Shen, Lei Zhang
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Feature extraction from ear-worn sensor data for gait analysis [PDF]
, 2014 Gait analysis has a significant role in assessing human's walking pattern. It is generally used in sports science for understanding body mechanics, and it is also used to monitor patients' neuro-disorder related gait abnormalities.
Atallah, Louis +3 more
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Energy Reports, 2022 Peak load forecasting plays an integral part in the planning and operating of energy plants for the utility companies and policymakers to devise reliable and stable power infrastructure.
M. Zulfiqar +4 more
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Permutation Inference for Canonical Correlation Analysis [PDF]
, 2020 Canonical correlation analysis (CCA) has become a key tool for population neuroimaging, allowing investigation of associations between many imaging and non-imaging measurements. As other variables are often a source of variability not of direct interest,
Nichols, Thomas E. +3 more
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Disambiguating the role of blood flow and global signal with partial information decomposition [PDF]
, 2019 Global signal (GS) is an ubiquitous construct in resting state functional magnetic resonance imaging (rs-fMRI), associated to nuisance, but containing by definition most of the neuronal signal.
Calhoun, Vince D. +5 more
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Mode decomposition-based time-varying phase synchronization for fMRI
NeuroImage, 2022 Recently, there has been significant interest in measuring time-varying functional connectivity (TVC) between different brain regions using resting-state functional magnetic resonance imaging (rs-fMRI) data.
Hamed Honari, Martin A. Lindquist
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智能科学与技术学报, 2020 The brain-computer interface is an emerging technology,which can analyze the collected motor imagery signals to control the external auxiliary equipment.A new method based on the noise-assisted fast multivariate empirical mode decomposition (NA-FMEMD ...
Qian ZHENG +6 more
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Penalized additive regression for space-time data: a Bayesian perspective [PDF]
, 2003 We propose extensions of penalized spline generalized additive models for analysing space-time regression data and study them from a Bayesian perspective.
Fahrmeir, Ludwig +2 more
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$k$-means clustering of extremes [PDF]
, 2019 The $k$-means clustering algorithm and its variant, the spherical $k$-means clustering, are among the most important and popular methods in unsupervised learning and pattern detection.
Janßen, Anja, Wan, Phyllis
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Applied Water Science, 2018 This paper proposes an alternative method for modeling stage–discharge relationships by accounting significant information from different process scales employing the multivariate empirical mode decomposition (MEMD).
S. Adarsh +6 more
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