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- W2065366397 abstract "Abstract In this paper, we analyze an evolving model with local information which can generate a class of networks by choosing different values of the parameter p . The model introduced exhibits the transition from unweighted networks to weighted networks because the distribution of the edge weight can be widely tuned. With the increase in the local information, the degree correlation of the network transforms from assortative to disassortative. We also study the distribution of the degree, strength and edge weight, which all show crossover between exponential and scale-free. Finally, an application of the proposed model to the study of the synchronization is considered. It is concluded that the synchronizability is enhanced when the heterogeneity of the edge weight is reduced." @default.
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- W2065366397 date "2007-11-01" @default.
- W2065366397 modified "2023-09-27" @default.
- W2065366397 title "From unweighted to weighted networks with local information" @default.
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- W2065366397 doi "https://doi.org/10.1016/j.physa.2007.06.022" @default.
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