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变时滞脉冲BAM神经网络的稳定性(英文) 被引量：1

Stability of Impulsive BAM Neural Networks with Time-varying Delays
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摘要 本文研究了当脉冲不太频繁易受大的脉冲影响下的时滞BAM神经网络具有唯一的指数稳定的平衡点.分析采用一个推广的比较原理和M-矩阵理论,得到一些关于唯一平衡点的收敛性的简单可行的充分条件.所得结果推广和改进了已有文献的结果. This paper demonstrates that there is an unique exponentially stable equilibrium state in a delay BAM neural networks that is subject to large impulses that are not too frequent.The analysis exploits a generalized comparison principle and M-matrix theory to derive some easily verifiable sufficient conditions for convergence to the unique globally stable equilibrium state.The results extend and improve earlier publications.
作者 高明
机构地区 包头师范学院数学科学学院
出处 《应用数学》 CSCD 北大核心 2012年第1期160-166,共7页 Mathematica Applicata
关键词 双向联想记忆神经网络 全局指数稳定性 脉冲 时滞 BAM neural networks Global exponential stability Impulses Delay
分类号 O175.21 [理学—基础数学]
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参考文献26

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应用数学
2012年 第1期

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