EEG Classification using Semi Supervised Learning IJTSRD
The major challenge in the current braincomputer interface research is the accurate classification of time varying electroencephalographic EEG signals. The labeled EEG samples are usually scarce, while the unlabeled samples are available in large quantities and easy to collect in real applications. Semi supervised learning SSL methods can utilize both labeled and unlabeled data to […]