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多时滞Cohen-Grossberg神经网络鲁棒稳定性的新判据 被引量：5

New Criteria for Robust Stability of Cohen-Grossberg Neural Networks with Multiple Delays
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摘要 分析了一类具有多时滞及参数摄动的Cohen-Grossberg神经网络的全局鲁棒稳定性.通过构造适当的Lyapunov泛函,以线性矩阵不等式形式给出了平衡点全局鲁棒稳定的判据.此外,所有结论的建立都不需要假定互连矩阵的对称性及激活函数的可微性和单调性.仿真结果进一步证明了结论的有效性. Global robust stability of a class of Cohen-Grossberg neural networks with multiple delays and parameter perturbations is analyzed.By way of constructing a suitable Lyapunov functional,the criteria expressed by the form of linear matrix inequality （LMI） are given for the global robust stability of equilibrium point.In addition,all results are established without assuming any symmetry of the interconnecting matrix, and the differentiability and monotonicity of activation functions. The simulation samples have proved the effectiveness of the conclusion.
作者 季策 张化光 关焕新
机构地区 东北大学信息科学与工程学院
出处 《电子学报》 EI CAS CSCD 北大核心 2007年第1期135-140,共6页 Acta Electronica Sinica
基金 国家自然科学基金(No.60325311 60534010 60572070 60671050) 长江学者和创新团队发展计划基金
关键词 COHEN-GROSSBERG神经网络 多时滞 参数摄动 鲁棒稳定性 线性矩阵不等式(LMI) Eyapunov泛函 cohen-grossberg neural networks multiple delays parameter perturbatons robust stability linear matrix inequality（LMI） lyapunov functional
分类号 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10

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二级参考文献6

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共引文献3

同被引文献46

引证文献5

二级引证文献3

电子学报
2007年 第1期

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