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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...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2015
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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. |
format | Online Article Text |
id | pubmed-4388559 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
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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