Mean-field and non-mean-field behaviors in scale-free networks with random boolean dynamics

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MetadadosDescriçãoIdioma
Autor(es): dc.creatorSilva, Alcides Volpato Carneiro de Castro e-
Autor(es): dc.creatorSilva, Jafferson Kamphorst Leal da-
Data de aceite: dc.date.accessioned2019-11-06T13:24:00Z-
Data de disponibilização: dc.date.available2019-11-06T13:24:00Z-
Data de envio: dc.date.issued2012-06-19-
Data de envio: dc.date.issued2012-06-19-
Data de envio: dc.date.issued2010-
Fonte completa do material: dc.identifierhttp://hdl.handle.net/123456789/878-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/capes/554592-
Descrição: dc.descriptionWe study two types of simplified Boolean dynamics in scale-free networks, both with synchronous update. Assigning only Boolean functions AND and XOR to the nodes with probability 1 − p and p, respectively, we are able to analyze the density of 1’s and the Hamming distance on the network by numerical simulations and by a mean-field approximation (annealed approximation). We show that the behavior is quite different if the node always enters in the dynamics as its own input (self-regulation) or not. The same conclusion holds for the Kauffman NK model. Moreover, the simulation results and the mean-field ones (i) agree well when there is no self-regulation, and (ii) disagree for small p when self-regulation is present in the model.-
Idioma: dc.languageen-
Título: dc.titleMean-field and non-mean-field behaviors in scale-free networks with random boolean dynamics-
Aparece nas coleções:Repositório Institucional - UFOP

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