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arXiv · 2410.15867

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

A. Elmwafy·José J. Oliveira·César M. Silva
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Abstract

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.

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A. Elmwafy, José J. Oliveira, César M. Silva. 2024-10-21. Convergence of asymptotic systems in Cohen-Grossberg neural network models with unbounded delays. https://arxiv.org/abs/2410.15867

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