Application of identity vectors for EEG classification.
Journal:
Journal of neuroscience methods
Published Date:
Jan 1, 2019
Abstract
BACKGROUND: Finding an optimal EEG subject verification algorithm is a long standing goal within the EEG community. For every advancement made, another feature set, classifier, or dataset is often introduced; tracking improvements in classification without a consistent benchmark, such as a classifier-feature pairing tested on a publicly available dataset, makes it difficult to understand how and why these improvements occur.