东北大学学报（自然科学版）

东北大学学报(自然科学版) ›› 2010, Vol. 31 ›› Issue (3): 309-312.DOI: -

• 论著 • 上一篇    下一篇

非负放大函数与多延时的Cohen-Grossberg神经网络的鲁棒稳定性

金英秀;王占山;冯健;   

  1. 东北大学信息科学与工程学院;
  • 收稿日期:2013-06-20 修回日期:2013-06-20 发布日期:2013-06-20
  • 通讯作者: -
  • 作者简介:-
  • 基金资助:
    国家自然科学基金资助项目(60774093);;

Robust stability analysis of Cohen-Grossberg neural networks with nonnegative amplification function and multiple delays

Kim, Yong-Su (1); Wang, Zhan-Shan (1); Feng, Jian (1)   

  1. (1) School of Information Science and Engineering, Northeastern University, Shenyang 110004, China
  • Received:2013-06-20 Revised:2013-06-20 Published:2013-06-20
  • Contact: Wang, Z.-S.
  • About author:-
  • Supported by:
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摘要： 在Cohen-Grossberg神经网络设计及实现过程中,非负放大函数条件是很实用的.在网络参数存在摄动的情况下,研究了具有非负放大函数的一类多延时Cohen-Grossberg神经网络的鲁棒渐近稳定性问题.首先通过证明一个有用的引理,建立了渐近稳定性和鲁棒稳定性之间的关系.其次,在不要求激励函数满足严格单调增加和有界性的情况下,通过构造适当的Lyapunov泛函,针对所研究的神经网络模型,基于线性矩阵不等式技术建立了平衡点鲁棒稳定的一个充分判据.仿真结果进一步证明了所得结论的有效性.

关键词: Cohen-Grossberg神经网络, 非负放大函数, 鲁棒稳定, 渐近稳定, 多延时

Abstract: In the process of design and implementation of Cohen-Grossberg neural networks, the nonnegative amplification function condition is very practicable. The robust asymptotic stability of a class of Cohen-Grossberg neural networks with nonnegative amplification function and multiple time delays is investigated in case of parameter perturbation. With a useful lemma proved, the relation between global asymptotic stability and robust stability is established. Then with no strictly monotonic increasing quantity and boundedness required for the activation function, a suitable Lyapunov functional is framed properly to give a sufficient and robustly stable criterion in form of linear matrix inequality (LMI) for the equilibrium point of the concerned Cohen-Grossberg neural networks. Simulation result verify the effectiveness of the conclusion.

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