Results 41 to 50 of about 1,866,810 (170)
Fault Detection of Electric Motors via Symmetrized Dot Pattern‐Based Features
International Journal of Mechanical System Dynamics, EarlyView.ABSTRACT This study proposes a novel symmetrized dot pattern (SDP) approach using designed SDP‐based features, extracted from transformed vibration signals, for fault detection. These features describe the compactness, inclination, and shape of the “snowflake” diagram distributions.
Mario Spirto +6 more
wiley +1 more source
CAAI Transactions on Intelligence Technology, EarlyView.ABSTRACT Accurate load forecasting and reliable anomaly detection are critical for the stable operation of modern smart grids (SGs), which increasingly rely on cyber‐connected infrastructures. However, the integration of smart metres and two‐way communication exposes SGs to data integrity attacks that can manipulate consumption measurements, degrade ...
Murad Ali Khan +4 more
wiley +1 more source
Seizure classification in EEG signals utilizing Hilbert-Huang transform
BioMedical Engineering OnLine, 2011 Background Classification method capable of recognizing abnormal activities of the brain functionality are either brain imaging or brain signal analysis.
Abdulhay Enas W, Oweis Rami J
doaj +1 more source
The Distributional Effects of Economic Uncertainty*
International Economic Review, EarlyView.ABSTRACT We study the distributional implications of uncertainty shocks by developing a model that links macroeconomic aggregates to the US distribution of earnings and consumption. Our findings suggest that the fraction of low‐earning workers decreases initially, while the share of households reporting low consumption increases.
Florian Huber +2 more
wiley +1 more source
Testing Distributional Granger Causality With Entropic Optimal Transport
Journal of Time Series Analysis, EarlyView.ABSTRACT We develop a novel nonparametric test for Granger causality in distribution based on entropic optimal transport. Unlike classical mean‐based approaches, the proposed method directly compares the full conditional distributions of a response variable with and without the history of a candidate predictor.
Tao Wang
wiley +1 more source
New Hilbert-Huang transform associated with linear canonical transform
四川大学学报. 自然科学版, 2016 Hilbert-Huang transform is an efficient non-stationary signal analysis tool. In its processing, two aspects are included: (i) empirical mode decomposition; (ii) Hilbert spectral analysis.
LIU Lu-Bo, LUO Mao-Kang, LAI Li
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Energies, 2017 The analysis of electrical signals is a pressing requirement for the optimal design of power distribution. In this context, this paper illustrates how to use a variety of numerical tools, such as the Fourier, wavelet, and Hilbert-Huang transforms, to ...
Vito Puliafito +2 more
doaj +1 more source
Signals, 2023 This study investigates the use of empirical mode decomposition (EMD) to extract intrinsic mode functions (IMFs) for the spectral analysis of EEG signals in healthy individuals and its possible biological interpretations. Unlike traditional EEG analysis,
Eduardo Arrufat-Pié +5 more
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Sparse Causal Dynamic Linear Regression
Journal of Time Series Analysis, EarlyView.ABSTRACT We develop a sparse causal dynamic regression framework for long multivariate time series. With very long time series, the potentially large number of lags and leads in a dynamic regression model often makes time‐domain estimation numerically unstable or intractable.
Rui Huang, Kung‐Sik Chan
wiley +1 more source
Classification and Identification of Underwater Target based on Sound Propagation
نشریه مهندسی دریا, 2018 This paper investigates an underwater noise target classification algorithm in order to identify vessels in shallow water. To this aim the Hilbert Huang transform has been used to extract features in order to be used in a classifier.
Hassan Sayyaadi +2 more
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