AIMC Topic: Time Factors

Clear Filters Showing 561 to 570 of 2001 articles

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...

Fixed-Time Synchronization of Competitive Neural Networks With Multiple Time Scales.

IEEE transactions on neural networks and learning systems
In this brief, we investigate the fixed-time synchronization of competitive neural networks with multiple time scales. These neural networks play an important role in visual processing, pattern recognition, neural computing, and so on. Our main contr...

Boundary Stabilization of Stochastic Delayed Cohen-Grossberg Neural Networks With Diffusion Terms.

IEEE transactions on neural networks and learning systems
This study considers the boundary stabilization for stochastic delayed Cohen-Grossberg neural networks (SDCGNNs) with diffusion terms by the Lyapunov functional method. In the realization of NNs, sometimes time delays and diffusion phenomenon cannot ...

Multivariate time-series classification with hierarchical variational graph pooling.

Neural networks : the official journal of the International Neural Network Society
In recent years, multivariate time-series classification (MTSC) has attracted considerable attention owing to the advancement of sensing technology. Existing deep-learning-based MTSC techniques, which mostly rely on convolutional or recurrent neural ...

Deep Unsupervised Domain Adaptation with Time Series Sensor Data: A Survey.

Sensors (Basel, Switzerland)
Sensors are devices that output signals for sensing physical phenomena and are widely used in all aspects of our social production activities. The continuous recording of physical parameters allows effective analysis of the operational status of the ...

Fixed-time projective synchronization of delayed memristive neural networks via aperiodically semi-intermittent switching control.

ISA transactions
This paper studies the fixed-time projective synchronization problem for a class of delayed memristive neural networks via aperiodically semi-intermittent switching control. Instead of using the common traditional controller containing two power expo...