Convergence of asymptotic systems in Cohen-Grossberg neural network models with unbounded delays
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arXiv
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| Format: | Preprint |
| Published: |
2024
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| _version_ | 1866914981781438464 |
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| author | Elmwafy, A. Oliveira, José J. Silva, César M. |
| author_facet | Elmwafy, A. Oliveira, José J. Silva, César M. |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2410_15867 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Convergence of asymptotic systems in Cohen-Grossberg neural network models with unbounded delays Elmwafy, A. Oliveira, José J. Silva, César M. Dynamical Systems 34K14, 34K20, 34K25, 34K60, 92B20 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. |
| title | Convergence of asymptotic systems in Cohen-Grossberg neural network models with unbounded delays |
| topic | Dynamical Systems 34K14, 34K20, 34K25, 34K60, 92B20 |
| url | https://arxiv.org/abs/2410.15867 |