Exponential synchronization for reactiondiffusion networks with mixed delays in terms of p p -norm via intermittent driving
In this paper, the globally exponential synchronization for a class of reactiondiffusion neural networks with Dirichlet boundary conditions and mixed delays is investigated based on periodically intermittent control. Some new and useful synchronization criteria in terms of p p -norm are derived by introducing multi-parameters, using Lyapunov functional theory. Subsequently, a feasible region of the control parameters for each neuron is derived for the realization of exponential synchronization. Besides, according to the theoretical results, the influences of diffusion strengths and diffusion spaces on synchronization are analyzed and a very interesting fact is revealed that the synchronization of neural networks with reactiondiffusions is more easily realized than those of neural networks without reactiondiffusions. Finally, a reactiondiffusion chaotic network is given to demonstrate the effectiveness of the proposed control methods.
exponential synchronization reactiondiffusion neural networks intermittent control finite distributed delays diffusion effects