AI Medical Compendium Topic:
Time Factors

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Rich learning representations for human activity recognition: How to empower deep feature learning for biological time series.

Journal of biomedical informatics
Deep learning versus feature engineering has drawn significant attention specifically for applications where expertly crafted features have been used for decades. Human activity recognition is no exception where statistical and motion specific featur...

MEEMD Decomposition-Prediction-Reconstruction Model of Precipitation Time Series.

Sensors (Basel, Switzerland)
To address the problem of low prediction accuracy of precipitation time series data, an improved overall mean empirical modal decomposition-prediction-reconstruction model (MDPRM) is constructed in this paper. First, the non-stationary precipitation ...

Finite-time synchronization of reaction-diffusion memristive neural networks: A gain-scheduled integral sliding mode control scheme.

ISA transactions
The finite-time synchronization issue of reaction-diffusion memristive neural networks (RDMNNs) is studied in this paper. To better synchronize the parameter-varying drive and response systems, an innovative gain-scheduled integral sliding mode contr...

Adaptive Neural Network Fixed-Time Control Design for Bilateral Teleoperation With Time Delay.

IEEE transactions on cybernetics
In this article, subject to time-varying delay and uncertainties in dynamics, we propose a novel adaptive fixed-time control strategy for a class of nonlinear bilateral teleoperation systems. First, an adaptive control scheme is applied to estimate t...

Quasisynchronization for Neural Networks With Partial Constrained State Information via Intermittent Control Approach.

IEEE transactions on cybernetics
This work addresses quasisynchronization (QS) of the master-slave (MS) neural networks (NNs) with mismatched parameters. The logarithmic quantizer and the round-robin protocol (RRP) are used to deal with the limited communication channel (CC) capacit...

Time-Synchronized Control for Disturbed Systems.

IEEE transactions on cybernetics
Finite-time control is concerned with steering a system state to the origin before a certain settling-time limit, ignoring any consideration of when each state element converges relative to the others. In this article, a control problem called time-s...

A Fast Weighted Fuzzy C-Medoids Clustering for Time Series Data Based on P-Splines.

Sensors (Basel, Switzerland)
The rapid growth of digital information has produced massive amounts of time series data on rich features and most time series data are noisy and contain some outlier samples, which leads to a decline in the clustering effect. To efficiently discover...

Fault Prediction Based on Leakage Current in Contaminated Insulators Using Enhanced Time Series Forecasting Models.

Sensors (Basel, Switzerland)
To improve the monitoring of the electrical power grid, it is necessary to evaluate the influence of contamination in relation to leakage current and its progression to a disruptive discharge. In this paper, insulators were tested in a saline chamber...

A Conditional GAN for Generating Time Series Data for Stress Detection in Wearable Physiological Sensor Data.

Sensors (Basel, Switzerland)
Human-centered applications using wearable sensors in combination with machine learning have received a great deal of attention in the last couple of years. At the same time, wearable sensors have also evolved and are now able to accurately measure p...

Finite-Time Synchronization of Complex-Valued Memristive-Based Neural Networks via Hybrid Control.

IEEE transactions on neural networks and learning systems
The finite-time synchronization problem is investigated for the master-slave complex-valued memristive neural networks in this article. A novel Lyapunov-function based finite-time stability criterion with impulsive effects is proposed and utilized to...