STRENGTH DISTRIBUTION IN DERIVATIVE NETWORKS

Luciano Da Fontoura Costa () and Gonzalo Travieso ()
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Luciano Da Fontoura Costa: Instituto de Fí sica de São Carlos, Universidade de São Paulo, Caixa Postal 369, 13560-970, São Carlos, SP, Brazil
Gonzalo Travieso: Instituto de Fí sica de São Carlos, Universidade de São Paulo, Caixa Postal 369, 13560-970, São Carlos, SP, Brazil

International Journal of Modern Physics C (IJMPC), 2005, vol. 16, issue 07, 1097-1105

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 exponentγ 1if the fitness has no upper limit but a positive lower limit. Possible implications for neuronal networks topology and dynamics are also discussed.

Keywords: Complex networks; fitness; weighted diagraphs; strength distribution; node similarity (search for similar items in EconPapers)
Date: 2005
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DOI: 10.1142/S0129183105007765

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