Shi Yanchao, Zhu Peiyong
School of Applied Mathematics, University of Electronic Science and Technology of China, Chengdu 611731, China
Neural Comput. 2014 Sep;26(9):2005-24. doi: 10.1162/NECO_a_00629. Epub 2014 Jun 12.
We propose a feedback controller for the synchronization of stochastic competitive neural networks with different timescales and reaction-diffusion terms. By constructing a proper Lyapunov-Krasovskii functional, as well as employing stochastic analysis theory, the LaShall-type invariance principle for stochastic differential delay equations, and a linear matrix inequality (LMI) technique, a feedback controller is designed to achieve the asymptotical synchronization of coupled stochastic competitive neural networks. A simulation example is given to show the effectiveness of the theoretical results.
我们提出了一种用于具有不同时间尺度和反应扩散项的随机竞争神经网络同步的反馈控制器。通过构造一个适当的Lyapunov-Krasovskii泛函，以及运用随机分析理论、随机微分延迟方程的LaShall型不变性原理和线性矩阵不等式（LMI）技术，设计了一个反馈控制器以实现耦合随机竞争神经网络的渐近同步。给出了一个仿真例子以说明理论结果的有效性。
