Using Genetic Algorithms for Automatic Recurrent ANN Development: an Application to EEG Signal Classification

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UDC.coleccionInvestigaciónes_ES
UDC.conferenceTitle5es_ES
UDC.departamentoCiencias da Computación e Tecnoloxías da Informaciónes_ES
UDC.endPage191es_ES
UDC.grupoInvRedes de Neuronas Artificiais e Sistemas Adaptativos -Informática Médica e Diagnóstico Radiolóxico (RNASA - IMEDIR)es_ES
UDC.journalTitleInternational Journal of Data Mining, Modelling and Managementes_ES
UDC.startPage182es_ES
UDC.volume2es_ES
dc.contributor.authorRivero, Daniel
dc.contributor.authorAguiar-Pulido, Vanessa
dc.contributor.authorFernández-Blanco, Enrique
dc.contributor.authorGestal, M.
dc.date.accessioned2018-05-14T09:58:08Z
dc.date.available2018-05-14T09:58:08Z
dc.date.issued2013
dc.description.abstract[Abstract] ANNs are one of the most successful learning systems. For this reason, many techniques have been published that allow the obtaining of feed-forward networks. However, fe w works describe techniques for developing recurrent networks. This work uses a genetic algorithm for automatic recurrent ANN devel opment. This system has been applied to solve a well-known problem: classi fication of EEG signals from epileptic patients. Results show the high performance of this system, and its ability to develop simple networks, with a low number of neurons and connections.es_ES
dc.description.sponsorshipRed Gallega de Investigación sobre Cáncer Colorrectal; ref. 2009/58es_ES
dc.description.sponsorshipPrograma Ibeoramericano de Ciencia y Tecnología para el Desarrollo; 209RT0366es_ES
dc.description.sponsorshipMinisterio de Industria, Turismo y Comercio; TSI-020110-2009-53es_ES
dc.description.sponsorshipXunta de Galicia; 10SIN105004PRes_ES
dc.description.sponsorshipInstituto de Salud Carlos III; PIO52048es_ES
dc.description.sponsorshipInstituto de Salud Carlos III; RD07/0067/0005es_ES
dc.identifier.citationRivero D, Aguiar-Pulido V, Fernández-Blanco E, Gestal M. Using genetic algorithms for automatic recurrent ANN development: an application to EEG signal classification. Int J Data Mining Modelling Management. 2013;5(2):182-191es_ES
dc.identifier.issn1759-1163
dc.identifier.issn1759-1171
dc.identifier.urihttp://hdl.handle.net/2183/20701
dc.language.isoenges_ES
dc.publisherIndersciencees_ES
dc.relation.urihttps://doi.org/10.1504/IJDMMM.2013.053695es_ES
dc.rights.accessRightsopen accesses_ES
dc.subjectArtificial neural networkses_ES
dc.subjectANNses_ES
dc.subjectGenetic algorithmses_ES
dc.subjectGAses_ES
dc.subjectSignal classificationes_ES
dc.subjectEpilepsy detectiones_ES
dc.titleUsing Genetic Algorithms for Automatic Recurrent ANN Development: an Application to EEG Signal Classificationes_ES
dc.typejournal articlees_ES
dspace.entity.typePublication
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relation.isAuthorOfPublication32e6ea1f-7cb0-4c6d-8345-cc8625f08574
relation.isAuthorOfPublication244a6828-de1c-45f3-86b6-69bb81250814
relation.isAuthorOfPublication65439986-7b8c-4418-b8e3-5694f520ecc7
relation.isAuthorOfPublication.latestForDiscoveryd8e10433-ea19-4a35-8cc6-0c7b9f143a6d

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