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  • 标题:Globally Exponential Stability of Impulsive Neural Networks with Given Convergence Rate
  • 本地全文:下载
  • 作者:Chengyan Liu ; Xiaodi Li ; Xilin Fu
  • 期刊名称:Advances in Artificial Neural Systems
  • 印刷版ISSN:1687-7594
  • 电子版ISSN:1687-7608
  • 出版年度:2013
  • 卷号:2013
  • DOI:10.1155/2013/908602
  • 出版社:Hindawi Publishing Corporation
  • 摘要:This paper deals with the stability problem for a class of impulsive neural networks. Some sufficient conditions which can guarantee the globally exponential stability of the addressed models with given convergence rate are derived by using Lyapunov function and impulsive analysis techniques. Finally, an example is given to show the effectiveness of the obtained results.
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