title: Exponential synchronization for reaction-diffusion networks with mixed delays in terms of p-norm via intermittent driving.
abstract: In this paper, the globally exponential synchronization for a class of reaction-diffusion 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-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 reaction-diffusions is more easily realized than those of neural networks without reaction-diffusions. Finally, a reaction-diffusion chaotic network is given to demonstrate the effectiveness of the proposed control methods.
authors.affiliation: College of Mathematics and System Sciences, Xinjiang University, Urumqi, Xinjiang 830046, PR China.
authors.forename: Cheng
authors.initials: C
authors.lastname: Hu
authors.forename: Juan
authors.initials: J
authors.lastname: Yu
authors.forename: Haijun
authors.initials: H
authors.lastname: Jiang
authors.forename: Zhidong
authors.initials: Z
authors.lastname: Teng
mesh_terms: D008959:Models, Neurological; D016571:Neural Networks, Computer; D013997:Time Factors