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Non-Homogeneous Fractal Hierarchical Weighted Networks

A model of fractal hierarchical structures that share the property of non-homogeneous weighted networks is introduced. These networks can be completely and analytically characterized in terms of the involved parameters, i.e., the size of the original graph N(k) and the non-homogeneous weight scaling...

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Detalles Bibliográficos
Autores principales: Dong, Yujuan, Dai, Meifeng, Ye, Dandan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4388559/
https://www.ncbi.nlm.nih.gov/pubmed/25849619
http://dx.doi.org/10.1371/journal.pone.0121946
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author Dong, Yujuan
Dai, Meifeng
Ye, Dandan
author_facet Dong, Yujuan
Dai, Meifeng
Ye, Dandan
author_sort Dong, Yujuan
collection PubMed
description A model of fractal hierarchical structures that share the property of non-homogeneous weighted networks is introduced. These networks can be completely and analytically characterized in terms of the involved parameters, i.e., the size of the original graph N(k) and the non-homogeneous weight scaling factors r (1), r (2), · · · r(M). We also study the average weighted shortest path (AWSP), the average degree and the average node strength, taking place on the non-homogeneous hierarchical weighted networks. Moreover the AWSP is scrupulously calculated. We show that the AWSP depends on the number of copies and the sum of all non-homogeneous weight scaling factors in the infinite network order limit.
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spelling pubmed-43885592015-04-21 Non-Homogeneous Fractal Hierarchical Weighted Networks Dong, Yujuan Dai, Meifeng Ye, Dandan PLoS One Research Article A model of fractal hierarchical structures that share the property of non-homogeneous weighted networks is introduced. These networks can be completely and analytically characterized in terms of the involved parameters, i.e., the size of the original graph N(k) and the non-homogeneous weight scaling factors r (1), r (2), · · · r(M). We also study the average weighted shortest path (AWSP), the average degree and the average node strength, taking place on the non-homogeneous hierarchical weighted networks. Moreover the AWSP is scrupulously calculated. We show that the AWSP depends on the number of copies and the sum of all non-homogeneous weight scaling factors in the infinite network order limit. Public Library of Science 2015-04-07 /pmc/articles/PMC4388559/ /pubmed/25849619 http://dx.doi.org/10.1371/journal.pone.0121946 Text en © 2015 Dong et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Dong, Yujuan
Dai, Meifeng
Ye, Dandan
Non-Homogeneous Fractal Hierarchical Weighted Networks
title Non-Homogeneous Fractal Hierarchical Weighted Networks
title_full Non-Homogeneous Fractal Hierarchical Weighted Networks
title_fullStr Non-Homogeneous Fractal Hierarchical Weighted Networks
title_full_unstemmed Non-Homogeneous Fractal Hierarchical Weighted Networks
title_short Non-Homogeneous Fractal Hierarchical Weighted Networks
title_sort non-homogeneous fractal hierarchical weighted networks
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4388559/
https://www.ncbi.nlm.nih.gov/pubmed/25849619
http://dx.doi.org/10.1371/journal.pone.0121946
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