From mechanisms to markers: novel noninvasive EEG proxy markers of the neural excitation and inhibition system in humans
Brain function is a product of the balance between excitatory and inhibitory (E/I) brain
activity. Variation in the regulation of this activity is thought to give rise to normal variation in …
activity. Variation in the regulation of this activity is thought to give rise to normal variation in …
A review of Shannon and differential entropy rate estimation
A Feutrill, M Roughan - Entropy, 2021 - mdpi.com
In this paper, we present a review of Shannon and differential entropy rate estimation
techniques. Entropy rate, which measures the average information gain from a stochastic …
techniques. Entropy rate, which measures the average information gain from a stochastic …
Entropy measures, entropy estimators, and their performance in quantifying complex dynamics: Effects of artifacts, nonstationarity, and long-range correlations
Entropy measures are widely applied to quantify the complexity of dynamical systems in
diverse fields. However, the practical application of entropy methods is challenging, due to …
diverse fields. However, the practical application of entropy methods is challenging, due to …
Entropy measures in machine fault diagnosis: Insights and applications
Entropy, as a complexity measure, has been widely applied for time series analysis. One
preeminent example is the design of machine condition monitoring and industrial fault …
preeminent example is the design of machine condition monitoring and industrial fault …
An ensemble hybrid forecasting model for annual runoff based on sample entropy, secondary decomposition, and long short-term memory neural network
Accurate and consistent annual runoff prediction in a region is a hot topic in management,
optimization, and monitoring of water resources. A novel prediction model (ESMD-SE-WPD …
optimization, and monitoring of water resources. A novel prediction model (ESMD-SE-WPD …
Rate-independent detection of atrial fibrillation by statistical modeling of atrial activity
S Ladavich, B Ghoraani - Biomedical Signal Processing and Control, 2015 - Elsevier
In this study, we propose a P-wave absence (PWA) based method for atrial fibrillation (AF)
identification over a short duration of electrocardiogram (ECG). The algorithm constructs a …
identification over a short duration of electrocardiogram (ECG). The algorithm constructs a …
A robust deep convolutional neural network for the classification of abnormal cardiac rhythm using single lead electrocardiograms of variable length
R Kamaleswaran, R Mahajan… - Physiological …, 2018 - iopscience.iop.org
Objective: Atrial fibrillation (AF) is a major cause of hospitalization and death in the United
States. Moreover, as the average age of individuals increases around the world, early …
States. Moreover, as the average age of individuals increases around the world, early …
Big multi-step wind speed forecasting model based on secondary decomposition, ensemble method and error correction algorithm
Wind power is one of the most promising powers. Wind speed forecasting can eliminate the
harmful effect caused by the intermittent and fluctuation of wind power, and big multi-step …
harmful effect caused by the intermittent and fluctuation of wind power, and big multi-step …
Fuzzy dispersion entropy: A nonlinear measure for signal analysis
Entropy is a powerful tool for nonlinear analysis of time series. We have recently introduced
dispersion entropy (DispEn), which has widely drawn attention from researchers in a variety …
dispersion entropy (DispEn), which has widely drawn attention from researchers in a variety …
Health degradation monitoring and early fault diagnosis of a rolling bearing based on CEEMDAN and improved MMSE
Rolling bearings play a crucial role in rotary machinery systems, and their operating state
affects the entire mechanical system. In most cases, the fault of a rolling bearing can only be …
affects the entire mechanical system. In most cases, the fault of a rolling bearing can only be …