Convergence of Asymptotic Systems of Non-autonomous Neural Network Models with Infinite Distributed Delays
作者: José J. Oliveira
作者单位: 1Universidade do Minho
刊名: Journal of Nonlinear Science, 2017, Vol.27 (5), pp.1463-1486
来源数据库: Springer Nature Journal
DOI: 10.1007/s00332-017-9371-8
关键词: Neural networksUnbounded coefficientsBounded coefficientsInfinite distributed delaysBoundednessGlobal convergenceAsymptotic systems34K2034K2534K6092B20
英文摘要: In this paper, we investigate the global convergence of solutions of non-autonomous Hopfield neural network models with discrete time-varying delays, infinite distributed delays, and possible unbounded coefficient functions. Instead of using Lyapunov functionals, we explore intrinsic features between the non-autonomous systems and their asymptotic systems to ensure the boundedness and global convergence of the solutions of the studied models. Our results are new and complement known results in the literature. The theoretical analysis is illustrated with some examples and numerical simulations.
原始语种摘要: In this paper, we investigate the global convergence of solutions of non-autonomous Hopfield neural network models with discrete time-varying delays, infinite distributed delays, and possible unbounded coefficient functions. Instead of using Lyapunov functionals, we explore intrinsic features between the non-autonomous systems and their asymptotic systems to ensure the boundedness and global convergence of the solutions of the studied models. Our results are new and complement known results in the literature. The theoretical analysis is illustrated with some examples and numerical simulations.
全文获取路径: Springer Nature  (合作)
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影响因子:1.566 (2012)

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关键词翻译
关键词翻译
  • convergence 汇合
  • autonomous 自发的
  • distributed 分布的
  • boundedness 有界性
  • asymptotic 渐近的
  • illustrated 以…说明
  • investigate 
  • theoretical 理论的
  • explore 勘探
  • infinite 无穷的