moabb.pipelines.utils_deep_model.EEGNet#

moabb.pipelines.utils_deep_model.EEGNet(data, input_layer, filters_1=8, kernel_size=64, depth=2, dropout=0.5, activation='elu')[source]#

EEGNet block implementation as described in [1].

This implementation is taken from code by The Integrated Systems Laboratory of ETH Zurich at iis-eth-zurich/eeg-tcnet

We use the original parameter implemented on the paper.

Note that this implementation has not been verified by the original authors.

References

[1]

Lawhern, V. J., Solon, A. J., Waytowich, N. R., Gordon, S. M., Hung, C. P., & Lance, B. J. (2018). EEGNet: a compact convolutional neural network for EEG-based brain–computer interfaces. Journal of neural engineering, 15(5), 056013. https://doi.org/10.1088/1741-2552/aace8c