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文章基本信息

  • 标题:Global Exponential Stability of Antiperiodic Solutions for Discrete-Time Neural Networks with Mixed Delays and Impulses
  • 本地全文:下载
  • 作者:Xiaofeng Chen ; Qiankun Song
  • 期刊名称:Discrete Dynamics in Nature and Society
  • 印刷版ISSN:1026-0226
  • 电子版ISSN:1607-887X
  • 出版年度:2012
  • 卷号:2012
  • DOI:10.1155/2012/168375
  • 出版社:Hindawi Publishing Corporation
  • 摘要:The problem on global exponential stability of antiperiodic solution is investigated for a class of impulsive discrete-time neural networks with time-varying discrete delays and distributed delays. By constructing an appropriate Lyapunov-Krasovskii functional, and using the contraction mapping principle and the matrix inequality techniques, a new delay-dependent criterion for checking the existence, uniqueness, and global exponential stability of anti-periodic solution is derived in linear matrix inequalities (LMIs). Two simulation examples are given to show the effectiveness of the proposed result.
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