dc.creator | Thiyam, Deepa Beeta | es |
dc.creator | Cruces Álvarez, Sergio Antonio | es |
dc.creator | Olías Sánchez, Francisco Javier | es |
dc.creator | Cichocki, Andrzej | es |
dc.date.accessioned | 2017-05-24T15:00:00Z | |
dc.date.available | 2017-05-24T15:00:00Z | |
dc.date.issued | 2017-02-25 | |
dc.identifier.citation | Thiyam, D.B., Cruces Álvarez, S.A., Olías Sánchez, F.J. y Cichocki, A. (2017). Optimization of Alpha-Beta Log-Det Divergences and their Application in the Spatial Filtering of Two Class Motor Imagery Movements. Entropy, 19 (3), 1-40. | |
dc.identifier.issn | 1099-4300 | es |
dc.identifier.uri | http://hdl.handle.net/11441/60436 | |
dc.description.abstract | The Alpha-Beta Log-Det divergences for positive definite matrices are flexible divergences
that are parameterized by two real constants and are able to specialize several relevant classical cases
like the squared Riemannian metric, the Steins loss, the S-divergence, etc. A novel classification
criterion based on these divergences is optimized to address the problem of classification of the
motor imagery movements. This research paper is divided into three main sections in order to
address the above mentioned problem: (1) Firstly, it is proven that a suitable scaling of the class
conditional covariance matrices can be used to link the Common Spatial Pattern (CSP) solution with a
predefined number of spatial filters for each class and its representation as a divergence optimization
problem by making their different filter selection policies compatible; (2) A closed form formula for
the gradient of the Alpha-Beta Log-Det divergences is derived that allows to perform optimization
as well as easily use it in many practical applications; (3) Finally, in similarity with the work of
Samek et al. 2014, which proposed the robust spatial filtering of the motor imagery movements based
on the beta-divergence, the optimization of the Alpha-Beta Log-Det divergences is applied to this
problem. The resulting subspace algorithm provides a unified framework for testing the performance
and robustness of the several divergences in different scenarios. | es |
dc.description.sponsorship | Ministerio de Economía y Competitividad TEC2014-53103-P | es |
dc.format | application/pdf | es |
dc.language.iso | eng | es |
dc.publisher | MDPI | es |
dc.relation.ispartof | Entropy, 19 (3), 1-40. | |
dc.rights | Attribution-NonCommercial-NoDerivatives 4.0 Internacional | * |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | * |
dc.subject | Similarity measures | es |
dc.subject | Common Spatial Pattern (CSP) | es |
dc.subject | Generalized divergences for symmetric positive definite matrices | es |
dc.subject | Brain Computer Interface (BCI) | es |
dc.subject | Alpha-Beta Log-Det divergence | es |
dc.title | Optimization of Alpha-Beta Log-Det Divergences and their Application in the Spatial Filtering of Two Class Motor Imagery Movements | es |
dc.type | info:eu-repo/semantics/article | es |
dcterms.identifier | https://ror.org/03yxnpp24 | |
dc.type.version | info:eu-repo/semantics/publishedVersion | es |
dc.rights.accessRights | info:eu-repo/semantics/openAccess | es |
dc.contributor.affiliation | Universidad de Sevilla. Departamento de Teoría de la Señal y Comunicaciones | es |
dc.relation.projectID | info:eu-repo/grantAgreement/MINECO/TEC2014-53103-P | es |
dc.relation.publisherversion | http://dx.doi.org/10.3390/e19030089 | es |
dc.identifier.doi | 10.3390/e19030089 | |
idus.format.extent | 40 p. | es |
dc.journaltitle | Entropy | es |
dc.publication.volumen | 19 | es |
dc.publication.issue | 3 | es |
dc.publication.initialPage | 1 | es |
dc.publication.endPage | 40 | es |