Area of research
Cognitive Neuroscience · Cellular and Molecular Neuroscience
Research interest
Research interests include Computer science, Brain–computer interface, Canonical correlation, Pattern recognition (psychology), Information transfer, and Interface (matter).
Enhancing the performance of SSVEP-based BCIs by combining task-related component analysis and deep neural network
Combing Multiple Visual Stimuli to Enhance the Performance of VEP-Based Biometrics
A Canonical Correlation Analysis-Based Transfer Learning Framework for Enhancing the Performance of SSVEP-Based BCIs
A high-frequency SSVEP-BCI system based on a 360 Hz refresh rate
Interface, interaction, and intelligence in generalized brain–computer interfaces
A Training Data-Driven Canonical Correlation Analysis Algorithm for Designing Spatial Filters to Enhance Performance of SSVEP-Based BCIs
Maximum Signal Fraction Analysis for Enhancing Signal-to-Noise Ratio of EEG Signals in SSVEP-Based BCIs
A Novel c-VEP BCI Paradigm for Increasing the Number of Stimulus Targets Based on Grouping Modulation With Different Codes
Enhancing Detection of SSVEPs for a High-Speed Brain Speller Using Task-Related Component Analysis
A Benchmark Dataset for SSVEP-Based Brain–Computer Interfaces
High-speed spelling with a noninvasive brain–computer interface
Filter bank canonical correlation analysis for implementing a high-speed SSVEP-based brain–computer interface
Enhancing performances of SSVEP-based brain–computer interfaces via exploiting inter-subject information
Probabilistic Common Spatial Patterns for Multichannel EEG Analysis
A study of the existing problems of estimating the information transfer rate in online brain–computer interfaces