Abstract
In this paper, mathematical analysis is proposed on the synchronization problem for stochastic reaction-diffusion Cohen-Grossberg neural networks with Neumann boundary conditions. By introducing several important inequalities and using Lyapunov functional technique, some new synchronization criteria in terms of p-norm are derived under periodically intermittent control. Some previous known results in the literature are improved, and some restrictions on the mixed time-varying delays are removed. The influence of diffusion coefficients, diffusion space, stochastic perturbation and control width on synchronization is analyzed by the obtained synchronization criteria. Numerical simulations are presented to show the feasibility of the theoretical results.
Highlights
Synchronization introduced by Pecora and Carrol [ ] means two or more systems which are either chaotic or periodic and share a common dynamic behavior
Based on the above discussion, we are concerned with the combined effects of mixed time-varying delays, stochastic perturbation and spatial diffusion on the exponential synchronization of Cohen-Grossberg neural networks with Neumann boundary conditions in terms of p-norm via periodically intermittent control to improve the previous results
Remark In this paper, by introducing the important inequality ( . ) in Lemma . and using Lyapunov functional theory, the exponential synchronization criteria relying on diffusion coefficients and diffusion space are derived for the proposed Cohen-Grossberg neural networks with Neumann boundary conditions under the periodically intermittent control
Summary
Synchronization introduced by Pecora and Carrol [ ] means two or more systems which are either chaotic or periodic and share a common dynamic behavior. Many results with respect to the synchronization of Cohen-Grossberg neural networks have been obtained based on periodically intermittent control in recent years (see, for example, [ – ]). In [ ], the exponential synchronization of Cohen-Grossberg neural networks with time-varying delays was discussed based on periodically intermittent control: dui(t) dt
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