惯性忆阻神经网络预设时间同步控制

Predefined-time synchronization of inertial memristive neural networks

基于全新的控制协议,研究了同时具有惯性项和忆阻项的神经网络预设时间同步问题。文中所考虑的网络模型可以广泛应用于生物突触模拟,具有较好的生物神经网络特性。通过构造合适的Lyapunov函数,利用不等式技巧,提出了惯性忆阻神经网络预设时间同步准则。所提出的控制协议可以使系统在任意预先给定的时间内稳定,该时间与系统初值和控制参数等都无关。最后,通过数值仿真验证了所得理论结果的有效性。

Based on a novel control protocol,the synchronization problem of predefined-time of neural networks with inertia and memristor is studied.The network model considered in this paper can be widely used to simulate biological synapses,and has good biological neural network characteristics.This paper proposes a predefined-time synchronization criterion for inertial memristive neural networks by constructing a suitable Lyapunov function and using inequality technique.Meanwhile,the proposed control protocol can make the system stable in predefined-time,which is independent of the initial value and control parameters.Finally,the numerical simulation verifies the validity of the proposed theoretical results.