A novel training-free recognition method for SSVEP-based BCIs using dynamic window strategy
Abstract
Objective. Filter bank canonical correlation analysis (FBCCA) is a widely-used classification approach implemented in steady-state visual evoked potential (SSVEP)-based brain computer interfaces (BCIs). However, conventional detection algorithms for SSVEP recognition problems, including the FBCCA, were usually based on 'fixed window' strategy. That's to say, these algorithms always analyze data with fixed length. This study devoted to enhance...
Paper Details
Title
A novel training-free recognition method for SSVEP-based BCIs using dynamic window strategy
Published Date
Mar 8, 2021
Volume
18
Issue
3
Pages
036007 - 036007
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