Analyzing complex networks evolution through Information Theory quantifiers
A methodology to analyze dynamical changes in complex networks based on Information Theory quantifiers is proposed. The square root of the Jensen-Shannon divergence, a measure of dissimilarity between two probability distributions, and the MPR Statistical Complexity are used to quantify states in th...
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| Formato: | JOUR |
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| Acceso en línea: | http://hdl.handle.net/20.500.12110/paper_03759601_v375_n4_p801_Carpi |
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todo:paper_03759601_v375_n4_p801_Carpi2023-10-03T15:31:13Z Analyzing complex networks evolution through Information Theory quantifiers Carpi, L.C. Rosso, O.A. Saco, P.M. Ravetti, M.G. Complex networks Jensen-Shannon divergence Statistical complexity A methodology to analyze dynamical changes in complex networks based on Information Theory quantifiers is proposed. The square root of the Jensen-Shannon divergence, a measure of dissimilarity between two probability distributions, and the MPR Statistical Complexity are used to quantify states in the network evolution process. Three cases are analyzed, the Watts-Strogatz model, a gene network during the progression of Alzheimer's disease and a climate network for the Tropical Pacific region to study the El Niño/Southern Oscillation (ENSO) dynamic. We find that the proposed quantifiers are able not only to capture changes in the dynamics of the processes but also to quantify and compare states in their evolution. © 2010 Elsevier B.V. All rights reserved. JOUR info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by/2.5/ar http://hdl.handle.net/20.500.12110/paper_03759601_v375_n4_p801_Carpi |
| institution |
Universidad de Buenos Aires |
| institution_str |
I-28 |
| repository_str |
R-134 |
| collection |
Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA) |
| topic |
Complex networks Jensen-Shannon divergence Statistical complexity |
| spellingShingle |
Complex networks Jensen-Shannon divergence Statistical complexity Carpi, L.C. Rosso, O.A. Saco, P.M. Ravetti, M.G. Analyzing complex networks evolution through Information Theory quantifiers |
| topic_facet |
Complex networks Jensen-Shannon divergence Statistical complexity |
| description |
A methodology to analyze dynamical changes in complex networks based on Information Theory quantifiers is proposed. The square root of the Jensen-Shannon divergence, a measure of dissimilarity between two probability distributions, and the MPR Statistical Complexity are used to quantify states in the network evolution process. Three cases are analyzed, the Watts-Strogatz model, a gene network during the progression of Alzheimer's disease and a climate network for the Tropical Pacific region to study the El Niño/Southern Oscillation (ENSO) dynamic. We find that the proposed quantifiers are able not only to capture changes in the dynamics of the processes but also to quantify and compare states in their evolution. © 2010 Elsevier B.V. All rights reserved. |
| format |
JOUR |
| author |
Carpi, L.C. Rosso, O.A. Saco, P.M. Ravetti, M.G. |
| author_facet |
Carpi, L.C. Rosso, O.A. Saco, P.M. Ravetti, M.G. |
| author_sort |
Carpi, L.C. |
| title |
Analyzing complex networks evolution through Information Theory quantifiers |
| title_short |
Analyzing complex networks evolution through Information Theory quantifiers |
| title_full |
Analyzing complex networks evolution through Information Theory quantifiers |
| title_fullStr |
Analyzing complex networks evolution through Information Theory quantifiers |
| title_full_unstemmed |
Analyzing complex networks evolution through Information Theory quantifiers |
| title_sort |
analyzing complex networks evolution through information theory quantifiers |
| url |
http://hdl.handle.net/20.500.12110/paper_03759601_v375_n4_p801_Carpi |
| work_keys_str_mv |
AT carpilc analyzingcomplexnetworksevolutionthroughinformationtheoryquantifiers AT rossooa analyzingcomplexnetworksevolutionthroughinformationtheoryquantifiers AT sacopm analyzingcomplexnetworksevolutionthroughinformationtheoryquantifiers AT ravettimg analyzingcomplexnetworksevolutionthroughinformationtheoryquantifiers |
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