Multiway Canonical Correlation Analysis for Frequency Components Recognition in SSVEP-Based BCIs

@inproceedings{Zhang2011MultiwayCC,
  title={Multiway Canonical Correlation Analysis for Frequency Components Recognition in SSVEP-Based BCIs},
  author={Yu Zhang and Guoxu Zhou and Qibin Zhao and Akinari Onishi and Jing Jin and Xingyu Wang and Andrzej Cichocki},
  booktitle={ICONIP},
  year={2011}
}
Steady-state visual evoked potential (SSVEP)-based brain computer-interface (BCI) is one of the most popular BCI systems. An efficient SSVEP-based BCI system in shorter time with higher accuracy in recognizing SSVEP has been pursued by many studies. This paper introduces a novel multiway canonical correlation analysis (Multiway CCA) approach to recognize SSVEP. This approach is based on tensor CCA and focuses on multiway data arrays. Multiple CCAs are used to find appropriate reference signals… CONTINUE READING
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