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  • 标题:Anti-periodic behavior for quaternion-valued delayed cellular neural networks
  • 本地全文:下载
  • 作者:Zhenhua Duan ; Changjin 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/s13662-021-03327-7
  • 出版社:Hindawi Publishing Corporation
  • 摘要:In this manuscript, quaternion-valued delayed cellular neural networks are studied. Applying the continuation theorem of coincidence degree theory, inequality techniques and a Lyapunov function approach, a new sufficient condition that guarantees the existence and exponential stability of anti-periodic solutions for quaternion-valued delayed cellular neural networks is presented. The obtained results supplement some earlier publications that deal with the anti-periodic solutions of quaternion-valued neural networks with distributed delay or impulse or state-dependent delay or inertial term. Computer simulations are displayed to check the derived analytical results.
  • 关键词:Quaternion-valued delayed cellular neural networks ; Anti-periodic solution ; Exponential stability ; Time delay
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