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具有分布时滞的双向联想记忆型Cohen-Grossberg神经网络的全局指数稳定性(英文)

Global exponential stability of BAM type Cohen-Grossberg neural network with distributed delays
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摘要 通过利用李雅普洛夫函数和Halanay不等式研究了具有分布时滞的双向联想记忆型Cohen-Grossberg神经网络,得到平衡点存在性及全局指数稳定性、全局鲁棒指数稳定性的充分条件,最后通过实例验证了结论. A class of the bidirectional associative memory ( BAM) type Cohen-Grossberg neural network with distributed delays was considered by Lyapunov function and Halanay inequality .Some sufficient con-ditions about the existence of equilibrium point , globally exponential stability and globally exponentially robust stability were obtained .At last, an example was given to demonstrated the results .
出处 《仲恺农业工程学院学报》 CAS 2013年第4期47-50,共4页 Journal of Zhongkai University of Agriculture and Engineering
基金 Supported by National Natural Science Foundation of China(31071560) Natural Science Foundation of Guangdong Province(10151022501000004)
关键词 双向联想记忆型Cohen-Grossberg神经网络 稳定 分布时滞 bidirectional associative memory(BAM) type Cohen-Grossberg neural networks stability distributed delays
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参考文献1

  • 1Lin Wang,Xingfu Zou.Harmless delays in Cohen–Grossberg neural networks[J].Physica D: Nonlinear Phenomena.2002(2)

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