摘要
针对一类具有时滞的中立型驱动反应BAM神经网络,提出全局渐近同步性问题.不使用现有文献中传统的李雅普诺夫泛函、矩阵测度和线性矩阵不等式(LMI)等已被广泛应用于研究神经网络全局渐近同步性的方法,而是通过构造2个微分不等式U 1(t)和U 1(t),利用微分不等式方程和不等式技巧解出2个不等式,得到能够确保中立型驱动反应BAM神经网络全局渐近同步的两个新的充分条件.
We analyze the global asymptotic synchronization of a class of neutral-type driving response BAM neural networks with time delays.Instead of using the traditional methods such as Lyapunov functional method,matrix measure method and linear matrix inequality(LMI)method which have been widely applied,we obtained two novel sufficient conditions on global asymptotic synchronization of the neutral-type driving response BAM neural networks by constructing two differential inequalities U 1(t)and U 1(t),solving them by using differential inequality formula and inequality techniques.
作者
李东华
刘开宇
LI Donghua;LIU Kaiyu(College of Mathematics and Econometrics,Hunan University,Changsha,Hunan 410012,China)
出处
《经济数学》
2020年第1期20-24,共5页
Journal of Quantitative Economics
基金
湖南省高校创新平台开放基金(14K019)。
关键词
中立型驱动反应
BAM神经网络
全局渐近同步性
微分不等式
neutral-type driving response
BAM neural networks
global asymptotic synchronization
differential inequality
