一类随机时滞神经网络的牵制同步

Pinning Synchronization Control of Stochastic Neural Networks with Time Delays

运用Lyapunov函数方法和矩阵不等式理论,一类随机时滞神经网络的牵制同步解的全局渐进稳定性得到分析.在这类问题中,时滞是时变的,随机因素是有界的.相关结论不仅建立了一些容易验证的条件,并且给出了一个方法可以弥补原本不能实现牵制同步的神经网络的缺陷,使各个结点达到同步状态.

By applying Lyapunov functional method and matrix inequality theory,the globally asymptotic stability of the pinning synchronous solution of stochastic neural networks with time delays is analyzed.The delays are time-invariant,and the random factors are norm bounded.Not only are some easily verifiable conditions established,but also a feasible way is given to offset the limitation of neural network in order to reach synchronization under pinning control.