braindecode.models.EEGNetv1#

class braindecode.models.EEGNetv1(in_chans, n_classes, input_window_samples=None, final_conv_length='auto', pool_mode='max', second_kernel_size=(2, 32), third_kernel_size=(8, 4), drop_prob=0.25)[source]#

EEGNet model from Lawhern et al. 2016.

See details in [EEGNet].

Parameters: in_chans (int) – XXX

Notes

This implementation is not guaranteed to be correct, has not been checked by original authors, only reimplemented from the paper description.

References

EEGNet: Lawhern, V. J., Solon, A. J., Waytowich, N. R., Gordon, S. M., Hung, C. P., & Lance, B. J. (2016). EEGNet: A Compact Convolutional Network for EEG-based Brain-Computer Interfaces. arXiv preprint arXiv:1611.08024.