Evaluating spiking neural models in the classification of motor imagery EEG signals using short calibration sessions

Simple item page
dc.contributor.authorR. Salazar-Varas
dc.contributor.authorRoberto A. Vázquez
dc.coverage.spatialBolivia
dc.date.accessioned2026-03-22T14:46:14Z
dc.date.available2026-03-22T14:46:14Z
dc.date.issued2018
dc.descriptionCitaciones: 17
dc.identifier.doi10.1016/j.asoc.2018.02.054
dc.identifier.urihttps://doi.org/10.1016/j.asoc.2018.02.054
dc.identifier.urihttps://andeanlibrary.org/handle/123456789/48442
dc.language.isoen
dc.publisherElsevier BV
dc.relation.ispartofApplied Soft Computing
dc.sourceUniversidad La Salle
dc.subjectBrain–computer interface
dc.subjectComputer science
dc.subjectElectroencephalography
dc.subjectRobustness (evolution)
dc.subjectArtificial intelligence
dc.subjectLinear discriminant analysis
dc.subjectPattern recognition (psychology)
dc.subjectMotor imagery
dc.subjectArtificial neural network
dc.subjectSupport vector machine
dc.titleEvaluating spiking neural models in the classification of motor imagery EEG signals using short calibration sessions
dc.typearticle

Files

Collections

Artículo Científico Publicado