Learning fuzzy models with a SAX-based partitioning for simulated seizure recognition

dc.contributor.author	Vergara García, Paula María
dc.contributor.author	Villar Flecha, José Ramón
dc.contributor.author	Cal Marín, Enrique Antonio de la
dc.contributor.author	Menéndez González, Manuel
dc.contributor.author	Sedano Franco, Javier
dc.date.accessioned	2017-03-06T13:17:20Z
dc.date.available	2017-03-06T13:17:20Z
dc.date.issued	2017
dc.identifier.citation	Advances in Intelligent Systems and Computing, 527, p. 20-30 (2017); doi:10.1007/978-3-319-47364-2_3
dc.identifier.isbn	9783319473635
dc.identifier.issn	2194-5357
dc.identifier.uri	https://www.scopus.com/inward/record.uri?eid=2-s2.0-84992448381&doi=10.1007%2f978-3-319-47364-2_3&partnerID=40&md5=d9fed93fba0f1d5687b96fea41fd94b9
dc.identifier.uri	http://hdl.handle.net/10651/40634
dc.description	International Conference on Soft Computing Models in Industrial and Environmental Applications, SOCO 2016, International Conference on Computational Intelligence in Security for Information Systems, CISIS 2016 and International Conference on European Transnational Education, ICEUTE 2016. 19 October 2016 through 21 October 2016
dc.format.extent	p. 20-30
dc.language.iso	eng
dc.publisher	Springer Verlag
dc.relation.ispartof	Advances in Intelligent Systems and Computing
dc.rights	©, Springer Verlag
dc.source	Scopus
dc.title	Learning fuzzy models with a SAX-based partitioning for simulated seizure recognition
dc.type	conference output	spa
dc.identifier.doi	10.1007/978-3-319-47364-2_3
dc.relation.publisherversion	http://dx.doi.org/10.1007/978-3-319-47364-2_3

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