Zhang Wei, Li Chuandong, Huang Tingwen, Xiao Mingqing
College of Computer Science, Chongqing University, Chongqing 400044, PR China.
Department of Mathematics, Texas A&M University at Qatar, Doha, P.O.Box 23874, Qatar.
Neural Netw. 2015 Nov;71:105-11. doi: 10.1016/j.neunet.2015.08.002. Epub 2015 Aug 17.
In this paper, the synchronization problem for neural networks with stochastic perturbation is studied with intermittent control via adaptive aperiodicity. Under the framework of stochastic theory and Lyapunov stability method, we develop some techniques of intermittent control with adaptive aperiodicity to achieve the synchronization of a class of neural networks, modeled by stochastic systems. Some effective sufficient conditions are established for the realization of synchronization of the underlying network. Numerical simulations of two examples are provided to illustrate the theoretical results obtained in the paper.
本文通过自适应非周期性间歇控制研究了具有随机扰动的神经网络的同步问题。在随机理论和李雅普诺夫稳定性方法的框架下，我们开发了一些自适应非周期性间歇控制技术，以实现一类由随机系统建模的神经网络的同步。建立了一些有效的充分条件来实现基础网络的同步。给出了两个例子的数值模拟，以说明本文得到的理论结果。
