具分布时滞和脉冲的BAM神经网络的全局指数稳定性  

Exponential Stability of BAM Neural Networks with Impulsive and Continuously Distributed Delays

作　　者：陈超[1] CHEN Chao(School of Science,Jimei University,Xiamen 361021,China)

机构地区：[1]集美大学理学院,福建厦门361021

出　　处：《集美大学学报（自然科学版）》2018年第4期305-311,共7页Journal of Jimei University：Natural Science

基　　金：国家自然科学基金项目(61573005)

摘　　要：讨论一类具有连续分布时滞和脉冲影响的双向联想记忆(bidirectional associative memory,BAM)神经网络,通过M-矩阵、谱理论以及建立脉冲时滞微分不等式,得到系统平衡点的存在唯一性及全局指数稳定性的充分判别条件。最后,给出一个实例,说明结论的可行性和有效性。In this paper,the global exponential stability of a bidirectional associative memory（ BAM） neural networks with impulses and continuously distributed delays were investigated. By using M-matrix,spectral theory and establishing an impulsive delay differential inequality,some new sufficient conditions for the existence and global exponential stability of the considered system were obtained. Finally,an example was given to illustrate the feasibility and effectiveness of the conclusion.

关 键 词：BAM神经网络 连续分布时滞 全局指数稳定性 

分 类 号：O175[理学—数学]