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  • 标题:Exponential stability for delayed complex-valued neural networks with reaction-diffusion terms
  • 本地全文:下载
  • 作者:Xiaohui Xu ; Jibin Yang ; Quan Xu
  • 期刊名称:Advances in Difference Equations
  • 印刷版ISSN:1687-1839
  • 电子版ISSN:1687-1847
  • 出版年度:2021
  • 卷号:2021
  • 期号:1
  • 页码:1
  • DOI:10.1186/s13662-020-03184-w
  • 出版社:Hindawi Publishing Corporation
  • 摘要:In this study, we investigate reaction-diffusion complex-valued neural networks with mixed delays. The mixed delays include both time-varying and infinite distributed delays. Criteria are derived to ensure the existence, uniqueness, and exponential stability of the equilibrium state of the addressed system on the basis of the M-matrix properties and homeomorphism mapping theories as well as the vector Lyapunov function method. The results demonstrate the positive effect of reaction-diffusion on the stability, which further improves the existing conditions. Finally, the analysis of several examples is compared to the present results to verify the correctness and reduced conservatism of the primary results.
  • 关键词:Complex-valued neural networks ; Reaction-diffusion terms ; Time-varying delays ; Infinite distributed delays ; Exponential stability ; Vector Lyapunov function method
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