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Using Genetic Algorithms for Automatic Recurrent ANN Development: an Application to EEG Signal Classification
dc.contributor.author | Rivero, Daniel | |
dc.contributor.author | Aguiar-Pulido, Vanessa | |
dc.contributor.author | Fernández-Blanco, Enrique | |
dc.contributor.author | Gestal, M. | |
dc.date.accessioned | 2018-05-14T09:58:08Z | |
dc.date.available | 2018-05-14T09:58:08Z | |
dc.date.issued | 2013 | |
dc.identifier.citation | Rivero 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):182-191 | es_ES |
dc.identifier.issn | 1759-1163 | |
dc.identifier.issn | 1759-1171 | |
dc.identifier.uri | http://hdl.handle.net/2183/20701 | |
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.sponsorship | Red Gallega de Investigación sobre Cáncer Colorrectal; ref. 2009/58 | es_ES |
dc.description.sponsorship | Programa Ibeoramericano de Ciencia y Tecnología para el Desarrollo; 209RT0366 | es_ES |
dc.description.sponsorship | Ministerio de Industria, Turismo y Comercio; TSI-020110-2009-53 | es_ES |
dc.description.sponsorship | Xunta de Galicia; 10SIN105004PR | es_ES |
dc.description.sponsorship | Instituto de Salud Carlos III; PIO52048 | es_ES |
dc.description.sponsorship | Instituto de Salud Carlos III; RD07/0067/0005 | es_ES |
dc.language.iso | eng | es_ES |
dc.publisher | Inderscience | es_ES |
dc.relation.uri | https://doi.org/10.1504/IJDMMM.2013.053695 | es_ES |
dc.subject | Artificial neural networks | es_ES |
dc.subject | ANNs | es_ES |
dc.subject | Genetic algorithms | es_ES |
dc.subject | GAs | es_ES |
dc.subject | Signal classification | es_ES |
dc.subject | Epilepsy detection | es_ES |
dc.title | Using Genetic Algorithms for Automatic Recurrent ANN Development: an Application to EEG Signal Classification | es_ES |
dc.type | info:eu-repo/semantics/article | es_ES |
dc.rights.access | info:eu-repo/semantics/openAccess | es_ES |
UDC.journalTitle | International Journal of Data Mining, Modelling and Management | es_ES |
UDC.volume | 2 | es_ES |
UDC.startPage | 182 | es_ES |
UDC.endPage | 191 | es_ES |
UDC.conferenceTitle | 5 | es_ES |
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