Maximizing the number of polychronous groups in spiking networks

Santana, Roberto, Larrañaga Múgica, Pedro María ORCID: https://orcid.org/0000-0002-1885-4501 and Bielza Lozoya, Maria Concepcion ORCID: https://orcid.org/0000-0001-7109-2668 (2012). Maximizing the number of polychronous groups in spiking networks. In: "14th Annual Genetic and Evolutionary Computation Conference (GECCO-2012)", 07/07/2012 - 11/07/2013, Philadelphia, PA, USA.. ISBN 978-1-4503-1178-6. pp. 1499-1500.

Description

Title: Maximizing the number of polychronous groups in spiking networks
Author/s:
Item Type: Presentation at Congress or Conference (Article)
Event Title: 14th Annual Genetic and Evolutionary Computation Conference (GECCO-2012)
Event Dates: 07/07/2012 - 11/07/2013
Event Location: Philadelphia, PA, USA.
Title of Book: Proceedings of the 14th Annual Genetic and Evolutionary Computation Conference (GECCO-2012)
Date: 2012
ISBN: 978-1-4503-1178-6
Subjects:
Freetext Keywords: polychronization, spiking neural network, estimation of distribution algorithm, perforación de redes neuronales, estimación de la distribución de algoritmos.
Faculty: Facultad de Informática (UPM)
Department: Inteligencia Artificial
Creative Commons Licenses: Recognition - No derivative works - Non commercial

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Abstract

In this paper we investigate the effect of biasing the axonal connection delay values in the number of polychronous groups produced for a spiking neuron network model. We use an estimation of distribution algorithm (EDA) that learns tree models to search for optimal delay configurations. Our results indicate that the introduced approach can be used to considerably increase the number of such groups.

More information

Item ID: 20294
DC Identifier: https://oa.upm.es/20294/
OAI Identifier: oai:oa.upm.es:20294
Official URL: http://dl.acm.org/citation.cfm?doid=2330784.233101...
Deposited by: Memoria Investigacion
Deposited on: 23 Oct 2013 17:01
Last Modified: 20 Feb 2023 08:50
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