Optimization of Alpha-Beta Log-Det Divergences and their Application in the Spatial Filtering of Two Class Motor Imagery Movements

Optimization of Alpha-Beta Log-Det Divergences and their Application in the Spatial Filtering of Two Class Motor Imagery Movements

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 crite...

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Bibliographic Details
Main Authors: Deepa Beeta Thiyam, Sergio Cruces, Javier Olias, Andrzej Cichocki
Format: Article
Language:English
Published: MDPI AG 2017-02-01
Series:Entropy
Subjects:
similarity measures
Common Spatial Pattern (CSP)
generalized divergences for symmetric positive definite matrices
Brain Computer Interface (BCI)
Alpha-Beta Log-Det divergence
Online Access:http://www.mdpi.com/1099-4300/19/3/89

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http://www.mdpi.com/1099-4300/19/3/89

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