Strength Distribution in Derivative Networks

Luciano da Fontoura Costa; Gonzalo Travieso

doi:10.1142/s0129183105007765

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Strength Distribution in Derivative Networks

Luciano da Fontoura Costa·Gonzalo Travieso

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Abstract

This article describes a complex network model whose weights are proportional to the difference between uniformly distributed ``fitness'' values assigned to the nodes. It is shown both analytically and experimentally that the strength density (i.e. the weighted node degree) for this model, called derivative complex networks, follows a power law with exponent $γ<1$ if the fitness has an upper limit and $γ>1$ if the fitness has no upper limit but a positive lower limit. Possible implications for neuronal networks topology and dynamics are also discussed.

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Luciano da Fontoura Costa, Gonzalo Travieso. 2005-01-11. Strength Distribution in Derivative Networks. https://doi.org/10.1142/s0129183105007765

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