5 research outputs found
Robust Exponential Stabilization of Stochastic Delay Interval Recurrent Neural Networks with Distributed Parameters and Markovian Jumping by Using Periodically Intermittent Control
We consider a class of stochastic delay recurrent neural networks with
distributed parameters and Markovian jumping. It is assumed that the coefficients in
these neural networks belong to the interval matrices. Several sufficient conditions
ensuring robust exponential stabilization are derived by using periodically intermittent control and Lyapunov functional. The obtained results are very easy to verify
and implement, and improve the existing results. Finally, an example with numerical
simulations is given to illustrate the presented criteria
Projective Lag Synchronization of Delayed Neural Networks Using Intermittent Linear State Feedback
The problem of projective lag synchronization of coupled neural networks with time delay is investigated. By means of the Lyapunov stability theory, an intermittent controller is designed for achieving projective lag synchronization between two delayed neural networks systems. Numerical simulations on coupled Lu neural systems illustrate the effectiveness of the results
Exponential synchronization for reaction-diffusion neural networks with mixed time-varying delays via periodically intermittent control
This paper deals with the exponential synchronization problem for reaction-diffusion neural networks with mixed time-varying delays and stochastic disturbance. By using stochastic analysis approaches and constructing a novel Lyapunov–Krasovskii functional, a periodically intermittent controller is first proposed to guarantee the exponential synchronization of reaction-diffusion neural networks with mixed time-varying delays and stochastic disturbance in terms of p-norm. The obtained synchronization results are easy to check and improve upon the existing ones. Particularly, the traditional assumptions on control width and time-varying delays are removed in this paper. This paper also presents two illustrative examples and uses simulated results of these examples to show the feasibility and effectiveness of the proposed scheme