TL;DR本文提出了一个基于 GAN 的端到端信号转换网络 TEGAN,用于数据长度扩展,能够生成人工 SSVEP 信号,应用于频率识别和深度学习等任务,能够显著提高传统和深度学习方法在有限校准数据下的分类性能,缩短校准时间并降低成本,具有高度实用性。
Abstract
Steady-state visual evoked potentials (ssveps) based brain-computer interface (BCI) has received considerable attention due to its high transfer rate and available quantity of targets. However, the performance of