具有随机扰动和不确定参数混杂时滞神经网络的自适应同步问题研究

Study on the adaptive synchronization of mixed time-lagging neutral network with uncertain parameters and random disturbances

基于驱动一响应同步原理和自适应控制原理,研究了一类具有不确定参数和随机干扰的混杂时滞神经网络的自适应同步问题。利用随机微分方程理论、Lyapunov稳定性理论,设计了不确定参数自适应更新规律,并得到神经网络系统达到几乎处处同步的充分条件。最后,数值仿真证明了所给方法的有效性。

Based on theories of synchronization of driving-response and adaptive control, the author studied the adaptive synchronization of mixed time-lagging neutral network with uncertain parameters and random disturbances. In this paper, with stochastic differential equation theory and Lyapunov stability theory, adaptive regeneration rule of uncertain parameters was designed and the sufficient condition of overall synchronization of neutral network system was found. At last, the validity of the proposed method was verified by the numerical simulation.