摘要 研究具有比例时滞Hopfield神经网络,通过非线性变换yi(t)=xi(et),将比例时滞Hopfield神经网络等价变换为常时滞Hopfield神经网络,构造合适的Lyapunov泛函,获得了保证Hopfield神经网络全局一致渐近稳定性的一个新的充分条件,并给出数值算例和仿真结果验证所得结论的正确性. The stability of Hopfield neural networks with proportional delays is studied.The transformation yi(t)=xi(et)transforms Hopfield neural networks with proportional delays into Hopfield neural networks with constant delays,and then constructing Lyapunov functionals.There new sufficient conditions can ensure global uniform asymptotic stability of this system is given.A numerical example and simulation is given to illustrate the correctness of the obtained result.
机构地区 伊犁师范大学数学与统计学院
出处 《伊犁师范学院学报:自然科学版》 2020年第4期13-17,共5页 Journal of Yili Normal University:Natural Science Edition
基金 国家自然科学基金项目(61663045).
关键词 HOPFIELD神经网络 比例时滞 全局一致渐近稳定性 LYAPUNOV泛函 Hopfield neural networks proportional delays global uniform asymptotic stability Lyapunov functional
