摘要
基于M-矩阵理论,探讨了一类带有分布式时滞神经网络系统的稳定性问题.在不需要激励函数有界和满足全局Lipschitz条件假设的前提下,得到了平衡点位置的估计问题;利用Dini导数和极限理论,得到两个全局渐近稳定性判据;最后利用仿真实例,说明了该判据的正确性.
Based on the M-matrix theory we discusses the stability problem for a class of neural networks with distributed delays.The estimates of equilibrium points problem is obtained without demanding the boundedness and globally Lipschitz condition of the activation functions,and two criteria for the global asymptotic stability are obtained by using the Dini derivative and limit theory.Finally,the simulation example is given to illustrate the effectiveness of the results.
出处
《延边大学学报（自然科学版）》
CAS
2013年第2期97-102,共6页
Journal of Yanbian University（Natural Science Edition）
基金
山东省优秀中青年科学家科研奖励基金资助项目(BS2010SF001)
关键词
时滞神经网络系统
全局稳定性
平衡点
M-矩阵
delayed neural networks
global asymptotic stability
equilibrium points
M-matrix
