具有混合时滞的脉冲复值神经网络的全局μ-稳定性

闫欢; 赵振江; 宋乾坤

doi:10.3879/j.issn.1000-0887.2015.07.008

具有混合时滞的脉冲复值神经网络的全局μ-稳定性

doi: 10.3879/j.issn.1000-0887.2015.07.008

¹重庆交通大学信息科学与工程学院,重庆 400074;²湖州师范学院数学系,浙江湖州 313000;³重庆交通大学数学系,重庆 400074

基金项目: 国家自然科学基金（61273021; 61473332）; 重庆市研究生科研创新项目(CYS14163)

详细信息

作者简介:
闫欢(1991—)，女，重庆万州人，硕士生(E-mail: huanyancquc@163.com);赵振江（1961—），男，新疆喀什人，教授，硕士(E-mail: zhaozjcn@163.com);宋乾坤(1963—)，男，四川岳池人，教授，博士(通讯作者. E-mail: qiankunsong@163.com).

中图分类号: O175.13
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出版历程
- 收稿日期: 2015-03-30
- 修回日期: 2015-06-10
- 刊出日期: 2015-07-15

Global μ-Stability of Impulsive Complex-Valued Neural Networks With Mixed Time-Varying Delays

¹School of Information Science and Engineering, Chongqing Jiaotong University, Chongqing 400074, P.R.China;²Department of Mathematics, Huzhou University, Huzhou, Zhejiang 313000, P.R.China;³Department of Mathematics, Chongqing Jiaotong University, Chongqing 400074, P.R.China

Funds: The National Natural Science Foundation of China(61273021; 61473332)

摘要

摘要: 研究了具有离散变化时滞和无界分布时滞的脉冲复值神经网络的稳定性，在所研究的神经网络中，活动函数仅仅要求满足Lipschitz条件.运用同胚映射原理，证明了具有混合时滞的脉冲复值神经网络平衡点的存在性和唯一性.通过构造Lyapunov-Krasovskii泛函，使用自由权矩阵方法和不等式技巧，获得了网络平衡点的全局μ-稳定性的充分性判据.数值仿真实例验证了结果的有效性.
- 复值神经网络 /
- 脉冲 /
- 变化时滞 /
- 全局μ-稳定性
Abstract: The global μ-stability of impulsive complex-valued neural networks with mixed time-varying delays was investigated. For the considered complex-valued neural networks, the activation functions only need to satisfy the Lipschitz conditions. Based on the homeomorphism mapping principle in the complex domain, a sufficient condition for the existence and uniqueness of the equilibrium point of the addressed complex-valued neural network was proposed in terms of linear matrix inequalities (LMIs). Through construction of appropriate Lyapunov-Krasovskii functionals, and with the free weighting matrix method and inequality technique, a delay-dependent criterion for checking the global μ-stability of the complex-valued neural networks was established in terms of LMIs. Finally, a simulation example was given to show the effectiveness of the obtained results.
- complex-valued neural network /
- impulsive /
- time-varying delay /
- global μ-stability

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参考文献(20)

[1]	廖晓昕. Hopfield型神经网络的稳定性[J]. 中国科学（A辑）, 1993,23(10): 1025-1035.(LIAO Xiao-xin. Stability of Hopfield neural networks[J]. Scientia Sinica Mathematica,1993,23(10): 1025-1035.(in Chinese))
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具有混合时滞的脉冲复值神经网络的全局μ-稳定性

doi: 10.3879/j.issn.1000-0887.2015.07.008

作者简介:
闫欢(1991—)，女，重庆万州人，硕士生(E-mail: huanyancquc@163.com);赵振江（1961—），男，新疆喀什人，教授，硕士(E-mail: zhaozjcn@163.com);宋乾坤(1963—)，男，四川岳池人，教授，博士(通讯作者. E-mail: qiankunsong@163.com).

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Global μ-Stability of Impulsive Complex-Valued Neural Networks With Mixed Time-Varying Delays

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具有混合时滞的脉冲复值神经网络的全局μ-稳定性

doi: 10.3879/j.issn.1000-0887.2015.07.008

作者简介: 闫欢(1991—)，女，重庆万州人，硕士生(E-mail: huanyancquc@163.com);赵振江（1961—），男，新疆喀什人，教授，硕士(E-mail: zhaozjcn@163.com);宋乾坤(1963—)，男，四川岳池人，教授，博士(通讯作者. E-mail: qiankunsong@163.com).

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出版历程

Global μ-Stability of Impulsive Complex-Valued Neural Networks With Mixed Time-Varying Delays

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出版历程

目录

作者简介:
闫欢(1991—)，女，重庆万州人，硕士生(E-mail: huanyancquc@163.com);赵振江（1961—），男，新疆喀什人，教授，硕士(E-mail: zhaozjcn@163.com);宋乾坤(1963—)，男，四川岳池人，教授，博士(通讯作者. E-mail: qiankunsong@163.com).