Analysis of biologically inspired small-world networks

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dc.contributor.author Aguirre, Carlos
dc.contributor.author Huerta, Ramón
dc.contributor.author Corbacho Abelaira, Fernando
dc.contributor.author Pascual, Pedro J.
dc.contributor.other UAM. Departamento de Ingeniería Informática es_ES
dc.date.accessioned 2015-03-17T19:02:42Z
dc.date.available 2015-03-17T19:02:42Z
dc.date.issued 2002
dc.identifier.citation Artificial Neural Networks — ICANN 2002: International Conference Madrid, Spain, August 28–30, 2002 Proceedings. Lecture Notes in Computer Science, Volumen 2415. Springer 2002. 27-32. en_US
dc.identifier.isbn 978-3-540-44074-1 (print) en_US
dc.identifier.isbn 978-3-540-46084-8 (online) en_US
dc.identifier.issn 0302-9743 (print) en_US
dc.identifier.issn 1611-3349 (online) en_US
dc.identifier.uri http://hdl.handle.net/10486/664629
dc.description The final publication is available at Springer via http://dx.doi.org/10.1007/3-540-46084-5_5 en_US
dc.description Proceedings of International Conference Madrid, Spain, August 28–30, 2002 en_US
dc.description.abstract Small-World networks are highly clusterized networks with small distances between their nodes. There are some well known biological networks that present this kind of connectivity. On the other hand, the usual models of Small-World networks make use of undirected and unweighted graphs in order to represent the connectivity between the nodes of the network. These kind of graphs cannot model some essential characteristics of neural networks as, for example, the direction or the weight of the synaptic connections. In this paper we analyze different kinds of directed graphs and show that they can also present a Small-World topology when they are shifted from regular to random. Also analytical expressions are given for the cluster coefficient and the characteristic path of these graphs. en_US
dc.description.sponsorship We thank the Ministerio de Ciencia y Tecnología (BFI 2000-015). (RH) was also funded by DE-FG03-96ER14092, (CA) was partially supported by ARO-MURI grant DAA655-98-1-0249 during a four month stay in UCSD. (PP) and (CA) are partially supported by PB98-0850 en_US
dc.format.extent 7 pág. es_ES
dc.format.mimetype application/pdf en
dc.language.iso eng en
dc.publisher Springer Berlin Heidelberg
dc.relation.ispartof Lecture Notes in Computer Science en_US
dc.rights © Springer-Verlag Berlin Heidelberg 2002
dc.subject.other Computation by Abstract Devices en_US
dc.subject.other Pattern Recognition en_US
dc.subject.other Image Processing and Computer Vision en_US
dc.subject.other Bioinformatics en_US
dc.subject.other Neurosciences en_US
dc.title Analysis of biologically inspired small-world networks en_US
dc.type conferenceObject en
dc.type bookPart en
dc.subject.eciencia Informática es_ES
dc.relation.publisherversion http://dx.doi.org/10.1007/3-540-46084-5_5
dc.identifier.doi 10.1007/3-540-46084-5_5
dc.identifier.publicationfirstpage 27
dc.identifier.publicationlastpage 32
dc.identifier.publicationvolume 2415
dc.relation.eventdate August 28–30, 2002 en_US
dc.relation.eventplace Madrid (Spain) en_US
dc.relation.eventtitle International Conference on Artificial Neural Networks, ICANN 2002 en_US
dc.type.version info:eu-repo/semantics/acceptedVersion en
dc.contributor.group Neurocomputación Biológica (ING EPS-005) es_ES
dc.rights.accessRights openAccess en
dc.authorUAM Huerta Rico, Ramón (259903)
dc.authorUAM Corbacho Abelaira , Fernando (267638)


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