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Existence and Exponential Stability of the Anti-Periodic Solutions for a Class of Impulsive CohenGrossberg Neural Networks with Mixed Delays
  • ISSN号:1003-6970
  • 期刊名称:《软件》
  • 时间:0
  • 分类:TP183[自动化与计算机技术—控制科学与工程;自动化与计算机技术—控制理论与控制工程]
  • 作者机构:[1]Department of Mathematics and Computer Science,Liuzhou Teachers College
  • 相关基金:supported by National Nature Science Foundation under Grant 11161029,China;science and technology research projects of guangxi under Grant 2013YB282,201203YB186
中文摘要:

In this paper,we study the anti-periodic solutions for a class of impulsive Cohen-Grossberg neural networks with mixed delays.By using analysis techniques,some sufficient conditions are obtained which guarantee the existence and global exponential stability of the anti-periodic solutions.The criteria extend and improve some earlier results.Moreover,we give an examples to illustrate our main results.

英文摘要:

In this paper,we study the anti-periodic solutions for a class of impulsive Cohen-Grossberg neural networks with mixed delays.By using analysis techniques,some sufficient conditions are obtained which guarantee the existence and global exponential stability of the anti-periodic solutions.The criteria extend and improve some earlier results.Moreover,we give an examples to illustrate our main results.

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期刊信息
  • 《软件:教学》
  • 主管单位:中国科学技术协会
  • 主办单位:中国电子学会 天津电子学会
  • 主编:胡锦华
  • 地址:北京市3105信箱
  • 邮编:100044
  • 邮箱:rjjxzz@126.com
  • 电话:010-56174511
  • 国际标准刊号:ISSN:1003-6970
  • 国内统一刊号:ISSN:12-9203/TP
  • 邮发代号:
  • 获奖情况:
  • 国内外数据库收录:
  • 波兰哥白尼索引
  • 被引量:305