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Deterministic hierarchical networks
dc.contributor.author | Barrière Figueroa, Eulalia |
dc.contributor.author | Comellas Padró, Francesc de Paula |
dc.contributor.author | Dalfó Simó, Cristina |
dc.contributor.author | Fiol Mora, Miquel Àngel |
dc.contributor.other | Universitat Politècnica de Catalunya. Departament de Matemàtiques |
dc.date.accessioned | 2016-09-14T12:16:25Z |
dc.date.available | 2017-05-03T00:30:22Z |
dc.date.issued | 2016 |
dc.identifier.citation | Barriere, E., Comellas, F., Dalfo, C., Fiol, M. Deterministic hierarchical networks. "Journal of physics A. Mathematical and theoretical", 2016, vol. 49, núm. 22, p. 1-19. |
dc.identifier.issn | 1751-8113 |
dc.identifier.uri | http://hdl.handle.net/2117/89918 |
dc.description.abstract | It has been shown that many networks associated with complex systems are small-world (they have both a large local clustering coefficient and a small diameter) and also scale-free (the degrees are distributed according to a power law). Moreover, these networks are very often hierarchical, as they describe the modularity of the systems that are modeled. Most of the studies for complex networks are based on stochastic methods. However, a deterministic method, with an exact determination of the main relevant parameters of the networks, has proven useful. Indeed, this approach complements and enhances the probabilistic and simulation techniques and, therefore, it provides a better understanding of the modeled systems. In this paper we find the radius, diameter, clustering coefficient and degree distribution of a generic family of deterministic hierarchical small-world scale-free networks that has been considered for modeling real-life complex systems. |
dc.format.extent | 19 p. |
dc.language.iso | eng |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/3.0/es/ |
dc.subject | Àrees temàtiques de la UPC::Matemàtiques i estadística::Investigació operativa::Programació matemàtica |
dc.subject.lcsh | Programming (Mathematics) |
dc.subject.lcsh | Artificial intelligence |
dc.subject.other | hierarchical network |
dc.subject.other | small-world |
dc.subject.other | scale-free |
dc.subject.other | degree |
dc.subject.other | diameter |
dc.subject.other | clustering |
dc.title | Deterministic hierarchical networks |
dc.type | Article |
dc.subject.lemac | Programació (Matemàtica) |
dc.subject.lemac | Intel·ligència artificial |
dc.contributor.group | Universitat Politècnica de Catalunya. COMBGRAPH - Combinatòria, Teoria de Grafs i Aplicacions |
dc.identifier.doi | 10.1088/1751-8113/49/22/225202 |
dc.description.peerreviewed | Peer Reviewed |
dc.subject.ams | Classificació AMS::65 Numerical analysis::65K Mathematical programming, optimization and variational techniques |
dc.subject.ams | Classificació AMS::68 Computer science::68T Artificial intelligence |
dc.rights.access | Open Access |
local.identifier.drac | 17750185 |
dc.description.version | Postprint (author's final draft) |
dc.relation.projectid | info:eu-repo/grantAgreement/MINECO//MTM2014-60127-P/ES/TECNICAS DE OPTIMIZACION EN TEORIA DE GRAFOS, GRUPOS Y COMBINATORIA. APLICACIONES A REDES, ALGORITMOS Y PROTOCOLOS DE COMUNICACION./ |
local.citation.author | Barriere, E.; Comellas, F.; Dalfo, C.; Fiol, M. |
local.citation.publicationName | Journal of physics A. Mathematical and theoretical |
local.citation.volume | 49 |
local.citation.number | 22 |
local.citation.startingPage | 1 |
local.citation.endingPage | 19 |
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