Averaged SSVEP recognition accuracies derived by the CCA, PCCA

Multi-information improves the performance of CCA-based SSVEP classification

Current Status, Challenges, and Possible Solutions of EEG-Based Brain-Computer Interface: A Comprehensive Review. - Abstract - Europe PMC

EEG-Based Brain-Computer Interfaces (BCIs): A Survey of Recent Studies on Signal Sensing Technologies and Computational Intelligence Approaches and Their Applications

PDF) Anti-noise Capability Improvement of Minimum Energy Combination Method for SSVEP Detection

Superresolution Image Reconstruction

SSVEP Enhancement Using Moving Average Filter Controlled by Phase Features

PDF) Comparison of EEG Signal Preprocessing Methods for SSVEP Recognition

High-speed spelling with a noninvasive brain–computer interface

Fractal based feature extraction technique for classifying EEG signal for color visualization tasks - IOS Press

EEG-Based Brain-Computer Interfaces (BCIs): A Survey of Recent Studies on Signal Sensing Technologies and Computational Intelligence Approaches and Their Applications

Frontiers A novel untrained SSVEP-EEG feature enhancement method using canonical correlation analysis and underdamped second-order stochastic resonance

International Journal of Neural Systems

Frequency Recognition in SSVEP-based BCI using Multiset Canonical Correlation Analysis – arXiv Vanity