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<p>In this paper, we investigate the convergence of asymptotic systems in non-autonomous Cohen–Grossberg neural network models, which include both infinite discrete time-varying and distributed delays. We derive stability results under conditions where the non-delay terms asymptotically dominate the delay terms. Several examples and a numerical simulation are provided to illustrate the significance and novelty of the main result.</p>

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Convergence of asymptotic systems in Cohen–Grossberg neural network models with unbounded delays

  • 期刊论文

  • 发表日期：

    2025年11月11日

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  • A. Elmwafy,
  • José J. Oliveira,
  • César M. Silva

摘要

In this paper, we investigate the convergence of asymptotic systems in non-autonomous Cohen–Grossberg neural network models, which include both infinite discrete time-varying and distributed delays. We derive stability results under conditions where the non-delay terms asymptotically dominate the delay terms. Several examples and a numerical simulation are provided to illustrate the significance and novelty of the main result.