Source:http://linkedlifedata.com/resource/pubmed/id/17995064
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| Predicate | Object |
|---|---|
| rdf:type | |
| lifeskim:mentions | |
| pubmed:issue |
4 Pt 2
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| pubmed:dateCreated |
2007-11-12
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| pubmed:abstractText |
Random networks are intensively used as null models to investigate properties of complex networks. We describe an efficient and accurate algorithm to generate arbitrarily two-point degree-degree correlated undirected random networks without self-edges or multiple edges among vertices. With the goal to systematically investigate the influence of two-point correlations, we furthermore develop a formalism to construct a joint degree distribution P(j,k) , which allows one to fix an arbitrary degree distribution P(k) and an arbitrary average nearest neighbor function k_{nn}(k) simultaneously. Using the presented algorithm, this formalism is demonstrated with scale-free networks [P(k) proportional, variantk;{-gamma}] and empirical complex networks [ P(k) taken from network] as examples. Finally, we generalize our algorithm to annealed networks which allows networks to be represented in a mean-field-like manner.
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| pubmed:language |
eng
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| pubmed:journal | |
| pubmed:status |
PubMed-not-MEDLINE
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| pubmed:month |
Oct
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| pubmed:issn |
1539-3755
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| pubmed:author | |
| pubmed:issnType |
Print
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| pubmed:volume |
76
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| pubmed:owner |
NLM
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| pubmed:authorsComplete |
Y
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| pubmed:pagination |
046111
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| pubmed:year |
2007
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| pubmed:articleTitle |
Generation of arbitrarily two-point-correlated random networks.
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| pubmed:affiliation |
Institut für Festkörperphysik, Technische Universität Darmstadt, Hochschulstrasse 8, 64289 Darmstadt, Germany.
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| pubmed:publicationType |
Journal Article
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