Impulsive effect on exponential synchronization of neural networks with leakage delay under sampled-data feedback control

Abstract

We consider the impulsive effect on the exponential synchronization of neural networks with leakage delay under the sampled-data feedback control. We use an appropriate Lyapunov-Krasovskii functional combined with the input delay approach and some inequality techniques to derive sufficient conditions that ensure the exponential synchronization of the delayed neural network. The conditions are formulated in terms of the leakage delay, the sampling period, and the exponential convergence rate. Numerical examples are given to demonstrate the usefulness and the effectiveness of the results.

Impulsive adaptive pinning synchronization of Lur'e networks with cluster‐tree topology via parameters variation protocols

“…Remark 7. As discussed above, impulsive control scheme, as one of the most important discrete-time control methods, [38][39][40] only actively works at each impulsive instant in a very sparse sequence of time. It should be noted that most of existing results about impulsive synchronization only focused on the positive impulsive effects or just take impulsive effects in some limited value ranges.…”

Exponential stability of impulsive systems with random delays under sampled‐data control

“…Xu and Chen [40] studied the problem of robust filtering for uncertain impulsive stochastic systems under sampled measurements. In [37], the impulsive effect on the exponential synchronisation of neural networks with leakage delay is investigated via sampled‐data feedback control. On the basis of the above, there is no result on the exponential stability problem of impulsive system with random time‐varying delays and non‐linear perturbations under the sampled‐data control in the previous literature.…”

New results for exponential synchronization of linearly coupled ordinary differential systems

“…Synchronization of linearly coupled ordinary differential equations (LCODEs) has been widely applied for decades to different fields, such as neuroscience, [1][2][3][4] economics, [5] biology, [6,7] ecology, [8] computer science, [9,10] and so on. Meanwhile, the synchronization technique for LCODEs has been favored by several researchers.…”