Logo do repositório
 
Publicação

Convergence of asymptotic systems with unbounded delays with applications to Cohen-Grossberg neural networks and Lotka-Volterra systems

datacite.subject.fosCiências Naturais::Matemáticas
dc.contributor.advisorSilva, César Augusto Teixeira Marques da
dc.contributor.advisorOliveira, José Joaquim Martins
dc.contributor.authorElmwafy, Ahmed Osama Mohamed Sayed Sayed
dc.date.accessioned2026-01-08T11:28:27Z
dc.date.available2026-01-08T11:28:27Z
dc.date.issued2025-11-20
dc.description.abstractThis thesis studies the dynamics of two prominent classes of models: Cohen-Grossberg neural network (CGNN) and Lotka-Volterra ecological systems. Firstly, we investigate the global exponential stability and the existence of a periodic solution of a general differential equation with unbounded distributed delays. The main stability criterion depends on the dominance of the non-delay terms over the delay terms. The criterion for the existence of a periodic solution is obtained by applying the coincidence degree theorem. We use the main results to obtain criteria for the existence and global exponential stability of periodic solutions of a generalized higher-order periodic CGNN model with discrete-time varying delays and infinite distributed delays. Moreover, we study the convergence of asymptotic systems in nonautonomous CGNN models. We derive stability results under conditions where the non-delay terms asymptotically dominate the delay terms. In the second part, we explore Lotka–Volterra-type ecological models with delays. We investigate the concept of permanence of a general delay differential system and apply it to a general Lotka-Volterra type model. Moreover, we obtain a partial result on the convergence of the system to its asymptotic systems. Additionally, we provide a comparison with results in the literature and numerical examples to illustrate the effectiveness of some of our results.eng
dc.description.abstractEsta tese estuda a dinâmica de duas classes proeminentes de modelos: modelos de redes neurais de Cohen-Grossberg e sistemas ecológicos de Lotka-Volterra. Na primeira parte da tese, fornecemos condições suficientes para a estabilidade exponencial global e a existência de uma solução periódica do seguinte sistema diferencial geral com atrasos distribuídos sem limites Cohen-Grossberg de ordem superior com atrasos discretos e distribuídos não necessariamente limitados [...]por
dc.identifier.tid101732066
dc.identifier.urihttp://hdl.handle.net/10400.6/19646
dc.language.isoeng
dc.relationConvergence of asymptotic systems: applications toneural network and biological models with delays
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/4.0/
dc.subjectEquação Diferencial Funcional
dc.subjectRede Neural de Cohen-Grossberg
dc.subjectModelo de Lotka-Volterra
dc.subjectAtraso Não Limitado
dc.subjectSolução Periódica
dc.subjectEstabilidade
dc.subjectConvergência de Modelos
dc.subjectSistema Assintótico
dc.subjectFunctional Differential Equation
dc.subjectCohen-Grossberg Neural Network
dc.subjectLotka-Volterra Model
dc.subjectUnbounded Delay
dc.subjectPeriodic Solution
dc.subjectStability
dc.subjectConvergence of Models
dc.subjectAsymptotic System
dc.titleConvergence of asymptotic systems with unbounded delays with applications to Cohen-Grossberg neural networks and Lotka-Volterra systemspor
dc.typedoctoral thesis
dspace.entity.typePublication
oaire.awardTitleConvergence of asymptotic systems: applications toneural network and biological models with delays
oaire.awardURIhttp://hdl.handle.net/10400.6/19645
person.familyNameElmwafy
person.givenNameAhmed Osama Mohamed Sayed Sayed
person.identifier.ciencia-id8912-B076-200B
person.identifier.gsidhttps://scholar.google.com/citations?user=FAKjcmAAAAAJ&hl=en
person.identifier.orcid0000-0001-5810-5401
relation.isAuthorOfPublication7c24bd85-3a16-40df-921d-856bf88b62b8
relation.isAuthorOfPublication.latestForDiscovery7c24bd85-3a16-40df-921d-856bf88b62b8
relation.isProjectOfPublication170b8a68-d4c2-4442-9690-16ff8452b0d6
relation.isProjectOfPublication.latestForDiscovery170b8a68-d4c2-4442-9690-16ff8452b0d6
thesis.degree.nameDoutoramento em Matemática e Aplicações

Ficheiros

Principais
A mostrar 1 - 1 de 1
A carregar...
Miniatura
Nome:
Tese-pos-defesa_signed.pdf
Tamanho:
1.07 MB
Formato:
Adobe Portable Document Format
Licença
A mostrar 1 - 1 de 1
Miniatura indisponível
Nome:
license.txt
Tamanho:
4.03 KB
Formato:
Item-specific license agreed upon to submission
Descrição: