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变时滞脉冲高阶BAM神经网络的指数稳定性

Exponential Stability of Impulsive High-order BAM Neural Networks with Time-varying Delays
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摘要 研究带脉冲和时滞项的高阶BAM神经网络系统的指数稳定性.首先,通过压缩映射原理得到了系统存在唯一的平衡点的新的充分条件.其次,利用Halanay不等式和数学归纳法,得到了保证系统指数稳定的充分条件.最后,通过一个例子说明所得结果的有效性. The paper investigated the exponential stability of high-order BAM neural networks with impul- sive effects and time-varying delays. New sufficient conditions ensuring the existence of a unique equilibrium point were achieved by contraction mapping principle. Then, by utilizing Halanay inequality and mathematical induction, some sufficient conditions that guarantee this system to be exponentially stable were obtained. Finally, one example was given to show the effectiveness of the results.
作者 高秀芝 王炳涛
机构地区 山东协和学院基础部 山东英才学院基础部
出处 《成都大学学报（自然科学版）》 2015年第3期240-246,共7页 Journal of Chengdu University（Natural Science Edition）
基金 山东省高等学校科技计划(J14LI51) 山东协和学院科技计划(XHXY201502)资助项目
关键词 BAM神经网络 全局指数稳定性 Halanay不等式 脉冲 时滞 BAM neural networks global exponential stability Halanay inequality impulse delays
分类号 O175.13 [理学—基础数学] TP183 [自动化与计算机技术—控制理论与控制工程]
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参考文献13

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成都大学学报（自然科学版）
2015年 第3期

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