Utilize este identificador para referenciar este registo:
https://hdl.handle.net/1822/78376
Título: | Global exponential stability of discrete-time Hopfield neural network models with unbounded delays |
Autor(es): | Oliveira, José J. |
Palavras-chave: | Neural networks Delay difference equations Unbounded delays Global stability |
Data: | 16-Mai-2022 |
Editora: | Taylor & Francis |
Revista: | Journal of Difference Equations and Applications |
Resumo(s): | In this paper, a general setting is presented to study the exponential stability of discrete-time systems with bounded or unbounded delays. Based on the M-matrix theory, we establish sufficient conditions to ensure the global exponential stability of the zero equilibrium of low-order, and high-order, discrete-time Hopfield neural network models with unbounded delays and delay in the leakage terms. A comparison of the literature shows that our results generalize and improve some in recent publications. |
Tipo: | Artigo |
URI: | https://hdl.handle.net/1822/78376 |
DOI: | 10.1080/10236198.2022.2073820 |
ISSN: | 1023-6198 |
e-ISSN: | 1563-5120 |
Versão da editora: | https://www.tandfonline.com/doi/full/10.1080/10236198.2022.2073820 |
Arbitragem científica: | yes |
Acesso: | Acesso aberto |
Aparece nas coleções: | CMAT - Artigos em revistas com arbitragem / Papers in peer review journals |
Ficheiros deste registo:
Ficheiro | Descrição | Tamanho | Formato | |
---|---|---|---|---|
manuscript-final-version.pdf | 830,74 kB | Adobe PDF | Ver/Abrir |