Strength distribution in gradient networks

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dc.creatorCosta, Luciano da Fontoura
dc.date2004-10-10
dc.date.accessioned2026-07-07T03:01:22Z
dc.date.available2026-07-07T03:01:22Z
dc.descriptionThis article describes a gradient complex network model whose weights are proportional to the difference between uniformly distributed ``fitness'' values assigned to the nodes. It is shown analytically and experimentally that the strength (i.e. the weighted node degree) density of such a network model can be well approximated by a power law with $γ\approx 0.35$. Possible implications for neuronal networks topology and dynamics are also discussed.
dc.description3 pages, 2 figures
dc.identifierhttps://arxiv.org/abs/cond-mat/0410230
dc.identifierhttp://arxiv.org/abs/cond-mat/0410230
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/25036
dc.subjectDisordered Systems and Neural Networks
dc.subjectStatistical Mechanics
dc.titleStrength distribution in gradient networks
dc.typetext

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