Gan Qintao
Department of Basic Science, Shijiazhuang Mechanical Engineering College, Shijiazhuang 050003, People's Republic of China.
Chaos. 2017 Jan;27(1):013113. doi: 10.1063/1.4973976.
In this paper, the exponential synchronization problem of generalized reaction-diffusion neural networks with mixed time-varying delays is investigated concerning Dirichlet boundary conditions in terms of p-norm. Under the framework of the Lyapunov stability method, stochastic theory, and mathematical analysis, some novel synchronization criteria are derived, and an aperiodically intermittent control strategy is proposed simultaneously. Moreover, the effects of diffusion coefficients, diffusion space, and stochastic perturbations on the synchronization process are explicitly expressed under the obtained conditions. Finally, some numerical simulations are performed to illustrate the feasibility of the proposed control strategy and show different synchronization dynamics under a periodically/aperiodically intermittent control.
本文针对具有混合时变延迟的广义反应扩散神经网络，在狄利克雷边界条件下，基于p范数研究其指数同步问题。在李雅普诺夫稳定性方法、随机理论和数学分析的框架下，推导了一些新颖的同步准则，并同时提出了一种非周期间歇控制策略。此外，在所获得的条件下，明确表达了扩散系数、扩散空间和随机扰动对同步过程的影响。最后，进行了一些数值模拟，以说明所提出控制策略的可行性，并展示在周期/非周期间歇控制下不同的同步动态。
