卷积步幅固定为1像素;凹凸层输入的空间填充是卷积后保持空间分辨率，即3×3凹凸层的填充为1像素。空间池化由五个最大池化层执行，它们遵循一些对流层(不是所有对流层都遵循最大池化)。最大池是在一个2×2像素的窗口上执行的，步长为2。
Also if you are getting "The regularizer is defined in Python, in which case it needs to be ported to TensorFlow.js or your JavaScript code." then replace manually replace all occurences of L2 to L1L2 which is mentioned here 'https://stackoverflow.com/questions/64063914/unknown-regularizer-...
Regardless, these regularizers assume a smooth or sparse connectivity structure of the brain, which may not always hold in practice [56]. Here, we introduce a novel deep learning approach for EEG-based MI classification: kernel-based regularized EEGNet (KREEGNet). Our approach addresses the ...