AIMC Topic: Time Factors

Clear Filters Showing 621 to 630 of 2001 articles

Lag H synchronization of coupled neural networks with multiple state couplings and multiple delayed state couplings.

Neural networks : the official journal of the International Neural Network Society
This paper mainly focuses on the lag H synchronization problem of coupled neural networks with multiple state or delayed state couplings. On one hand, by exploiting state feedback controller and Lyapunov functional, a criterion of lag H synchronizati...

Generative adversarial networks for biomedical time series forecasting and imputation.

Journal of biomedical informatics
In the present systematic review we identified and summarised current research activities in the field of time series forecasting and imputation with the help of generative adversarial networks (GANs). We differentiate between imputation which descri...

Path following Control of an Underactuated Catamaran for Recovery Maneuvers.

Sensors (Basel, Switzerland)
This paper focuses on the autonomous recovery maneuvers of an unknown underactuated practical catamaran, which returns to its initial position corresponding to the man overboard (MOB) by simply adjusting the rate of turn. This paper investigates the ...

Finite-Time Dynamic Allocation and Control in Multiagent Coordination for Target Tracking.

IEEE transactions on cybernetics
A new finite-time dynamic allocation and control scheme is developed in this article for multiple agents tracking a moving target. Based on a competitive manner, the dynamic allocation is achieved by k-winners-take-all (k-WTA), which can be realized ...

Finite-Time H Estimator Design for Switched Discrete-Time Delayed Neural Networks With Event-Triggered Strategy.

IEEE transactions on cybernetics
This article is concerned with the event-triggered finite-time H estimator design for a class of discrete-time switched neural networks (SNNs) with mixed time delays and packet dropouts. To further reduce the data transmission, both the measured info...

Event-triggered delayed impulsive control for nonlinear systems with application to complex neural networks.

Neural networks : the official journal of the International Neural Network Society
This paper studies the Lyapunov stability of nonlinear systems and the synchronization of complex neural networks in the framework of event-triggered delayed impulsive control (ETDIC), where the effect of time delays in impulses is fully considered. ...

A Time Series Forecasting Approach Based on Nonlinear Spiking Neural Systems.

International journal of neural systems
Nonlinear spiking neural P (NSNP) systems are a recently developed theoretical model, which is abstracted by nonlinear spiking mechanism of biological neurons. NSNP systems have a nonlinear structure and the potential to describe nonlinear dynamic sy...

Synchronization and state estimation for discrete-time coupled delayed complex-valued neural networks with random system parameters.

Neural networks : the official journal of the International Neural Network Society
In this paper, an array of discrete-time coupled complex-valued neural networks (CVNNs) with random system parameters and time-varying delays are introduced. The stochastic fluctuations of system parameters, which are characterized by a set of random...

Adversarial Joint-Learning Recurrent Neural Network for Incomplete Time Series Classification.

IEEE transactions on pattern analysis and machine intelligence
Incomplete time series classification (ITSC) is an important issue in time series analysis since temporal data often has missing values in practical applications. However, integrating imputation (replacing missing data) and classification within a mo...

Improved Stability Criteria for Delayed Neural Networks Using a Quadratic Function Negative-Definiteness Approach.

IEEE transactions on neural networks and learning systems
This brief is concerned with the stability of a neural network with a time-varying delay using the quadratic function negative-definiteness approach reported recently. A more general reciprocally convex combination inequality is taken to introduce so...