具有Dirichlet有界条件的反应扩散Cohen-Grossberg神经网络指数稳定性

Exponential stability of reaction-diffusion Cohen-Grossberg neural networks with Dirichlet boundary conditions

通过构造合适的Lyapunov泛函并结合数学分析技巧,讨论一类具有Dirichlet边界条件的基于马尔可夫切换的脉冲时滞反应扩散Cohen-Grossberg神经网络模型的指数稳定性。利用不等式技术和随机分析理论,得到了神经网络的指数稳定的若干充分判据。最后通过算例验证了所得到结果的有效性。

By constructing a suitable Lyapunov functional and combining it with mathematical analysis techniques,we discuss the exponential stability of impulsive time delay reaction-diffusion Cohen-Grossberg neural networks with Dirichlet boundary conditions and Markovian switching.Some sufficient criteria for exponential stability of neural networks are obtained by using the inequality technique and stochastic analysis theory.Finally,an example is given to verify the validity of the results.