Averaged SSVEP recognition accuracies derived by the CCA, PCCA
Descrição
EEG-Based Brain-Computer Interfaces (BCIs): A Survey of Recent Studies on Signal Sensing Technologies and Computational Intelligence Approaches and Their Applications
SSVEP Enhancement Using Moving Average Filter Controlled by Phase Features
Cross-subject fusion based on time-weighting canonical correlation analysis in SSVEP-BCIs - ScienceDirect
Full article: P300 Detection with Brain–Computer Interface Application Using PCA and Ensemble of Weighted SVMs
Brain Sciences, Free Full-Text
Frequency Recognition in SSVEP-based BCI using Multiset Canonical Correlation Analysis – arXiv Vanity
A classification algorithm of an SSVEP brain-Computer interface based on CCA fusion wavelet coefficients - ScienceDirect
Multi-information improves the performance of CCA-based SSVEP classification
Frequency Recognition in SSVEP-based BCI using Multiset Canonical Correlation Analysis – arXiv Vanity
A Comparison Study of Canonical Correlation Analysis Based Methods for Detecting Steady-State Visual Evoked Potentials
SSVEP Enhancement Using Moving Average Filter Controlled by Phase Features
Averaged SSVEP recognition accuracies derived by the CCA, PCCA, MwayCCA
Brain Sciences, Free Full-Text
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