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一类BAM神经网络的全局指数稳定性
引用本文:周庆华. 一类BAM神经网络的全局指数稳定性[J]. 肇庆学院学报, 2009, 30(2): 8-11
作者姓名:周庆华
作者单位:肇庆学院,数学与信息科学学院,广东,肇庆,526061
基金项目:肇庆学院青年科学研究基金 
摘    要:利用变参数方法和不等式技巧,研究了一类BAM神经网络的动力学特性,得到了能保证其平衡解唯一性和全局指数稳定性的条件,并且此条件与时滞无关.

关 键 词:双边联想记忆  指数稳定  变时滞  耗散

Global Exponential Stability of a Class of BAM Neural Networks
ZHOU Qinghua. Global Exponential Stability of a Class of BAM Neural Networks[J]. Journal of Zhaoqing University (Bimonthly), 2009, 30(2): 8-11
Authors:ZHOU Qinghua
Affiliation:ZHOU Qinghua (Faculty of Mathematics and Information Sciences, Zhaoqing University,Zhaoqing Guangdong 526061 ,China)
Abstract:The stability property of bidirectional associate memory (BAM) neural networks with timevarying delays and diffusion terms are considered. By using the method of variation parameter and inequality technique,the delay-independent sufficient conditions to guarantee the uniqueness and global exponential stability of the equilibrium solution of such networks are established.
Keywords:bidirectional associate memory  exponential stability  time-varying delay  diffusion
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