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dc.contributor.authorAguirre Maeso, Carlos 
dc.contributor.authorHuerta, Ramón
dc.contributor.authorCorbacho Abelaira, Fernando
dc.contributor.authorPascual Broncano, Pedro José 
dc.contributor.otherUAM. Departamento de Ingeniería Informáticaes_ES
dc.date.accessioned2015-03-17T19:02:42Z
dc.date.available2015-03-17T19:02:42Z
dc.date.issued2002
dc.identifier.citationArtificial 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.isbn978-3-540-44074-1 (print)en_US
dc.identifier.isbn978-3-540-46084-8 (online)en_US
dc.identifier.issn0302-9743 (print)en_US
dc.identifier.issn1611-3349 (online)en_US
dc.identifier.urihttp://hdl.handle.net/10486/664629
dc.descriptionThe final publication is available at Springer via http://dx.doi.org/10.1007/3-540-46084-5_5en_US
dc.descriptionProceedings of International Conference Madrid, Spain, August 28–30, 2002en_US
dc.description.abstractSmall-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.sponsorshipWe 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 PB98-0850en_US
dc.format.extent7 pág.es_ES
dc.format.mimetypeapplication/pdfen
dc.language.isoengen
dc.publisherSpringer Berlin Heidelberg
dc.relation.ispartofLecture Notes in Computer Scienceen_US
dc.rights© Springer-Verlag Berlin Heidelberg 2002
dc.subject.otherComputation by Abstract Devicesen_US
dc.subject.otherPattern Recognitionen_US
dc.subject.otherImage Processing and Computer Visionen_US
dc.subject.otherBioinformaticsen_US
dc.subject.otherNeurosciencesen_US
dc.titleAnalysis of biologically inspired small-world networksen_US
dc.typeconferenceObjecten
dc.typebookParten
dc.subject.ecienciaInformáticaes_ES
dc.relation.publisherversionhttp://dx.doi.org/10.1007/3-540-46084-5_5
dc.identifier.doi10.1007/3-540-46084-5_5
dc.identifier.publicationfirstpage27
dc.identifier.publicationlastpage32
dc.identifier.publicationvolume2415
dc.relation.eventdateAugust 28–30, 2002en_US
dc.relation.eventplaceMadrid (Spain)en_US
dc.relation.eventtitleInternational Conference on Artificial Neural Networks, ICANN 2002en_US
dc.type.versioninfo:eu-repo/semantics/acceptedVersionen
dc.contributor.groupNeurocomputación Biológica (ING EPS-005)es_ES
dc.rights.accessRightsopenAccessen
dc.authorUAMHuerta Rico, Ramón (259903)
dc.authorUAMCorbacho Abelaira , Fernando (267638)
dc.facultadUAMEscuela Politécnica Superior


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