Block activity in metric neural networks
Entity
UAM. Departamento de Ingeniería InformáticaPublisher
World Academy of Science, Engineering and TechnologyDate
2008-01-21Citation
Proceedings of the World Academy of Science, Engineering and Technology 2.1 (2008): 823-826ISSN
2010-376X (print); 2010-3778 (online)Funded by
This work was supported by TIN 2004-04363-CO03-03, TIN 2007-65989 and CAM S-SEM-0255-2006.Project
Comunidad de Madrid. S2006/SEM-0255/OLFACTOSENSEEditor's Version
http://waset.org/Publication/block-activity-in-metric-neural-networks/14975Subjects
Block attractor; Random interaction; Small world; Spin glass; InformáticaRights
© 2008 World Academy of Science, Engineering and TechnologyAbstract
The model of neural networks on the small-world
topology, with metric (local and random connectivity) is investigated.
The synaptic weights are random, driving the network towards a
chaotic state for the neural activity. An ordered macroscopic neuron
state is induced by a bias in the network connections. When the
connections are mainly local, the network emulates a block-like
structure. It is found that the topology and the bias compete to
influence the network to evolve into a global or a block activity
ordering, according to the initial conditions.
Files in this item
Google Scholar:González, Mario
-
Domínguez Carreta, David Renato
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Rodríguez Ortiz, Francisco Borja
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