含脉冲的变时滞静态神经网络的稳定性分析

Stability analysis for delay-dependent impulsive static neural networks with time-varying delays

研究含脉冲的变时滞静态神经网络模型的指数稳定性。通过构造恰当的Lyapunov泛函,利用线性矩阵不等式方法,给出了该神经网络模型在延迟依赖条件下的指数稳定性的充分条件。同时考虑时滞和脉冲的影响,因而考虑的情况更具普遍性,适用的范围更广。仿真例子说明所得结果适用范围宽,保守性小,易于验证的特点。

The global exponential stability of the static neural networks with impulsive effect and time-varying delays is investigated. By constructing Lyapunov functional and using linear matrix inequality approach, sufficient conditions for delay dependent exponential stability are obtained. The merit of the approach lies in its reduced conservatism, which is made by considering not only the effect of impulsive but also the time-varying delay. An example is given to illustrate the effectiveness of the theoretical results.