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dc.date.accessioned 2025-10-07T12:16:05Z
dc.date.available 2025-10-07T12:16:05Z
dc.date.issued 2003
dc.identifier.uri http://sedici.unlp.edu.ar/handle/10915/185600
dc.description.abstract We simulate an associative memory model using spiking neurons instead of McCulloch-Pitts neurons. To store a set of patterns, we employ a Hebbian-like learning algorithm. The learning behavior, however, is somewhat of a different one of the traditional Hopfield model. To study the difference we explore the fitness landscape defined on synaptic weights space when they evolve searching for the optimal learning. en
dc.language en es
dc.subject associative memory model es
dc.subject spiking neurons es
dc.subject learning behavior es
dc.title Can climbers take the uphill slope again?: a fitness landscape on weight space of an application using spiking neurons under rate coding en
dc.type Objeto de conferencia es
sedici.identifier.issn 1666-1079 es
sedici.creator.person Imada, Akira es
sedici.subject.materias Ciencias Informáticas es
sedici.description.fulltext true es
mods.originInfo.place Sociedad Argentina de Informática e Investigación Operativa es
sedici.subtype Objeto de conferencia es
sedici.rights.license Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
sedici.rights.uri http://creativecommons.org/licenses/by-nc-sa/4.0/
sedici.date.exposure 2003-09
sedici.relation.event Simposio Argentino de Inteligencia Artificial (ASAI 2003)- JAIIO 32 (CABA, 1 al 5 de septiembre de 2003) es
sedici.description.peerReview peer-review es


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Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) Except where otherwise noted, this item's license is described as Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)