In this article, a new DNN, one-dimensional residual convolutional autoencoder (1-DRCAE), is proposed for learning features from vibration signals directly in an unsupervised-learning way. First, 1-D ...

If the one-dimensional EEG signals are directly processed ... Network structure of the convolution autoencoder. As shown in Figure 8, the Conv1 layer is a convolution layer with an input by selecting ...

The structure of this conv autoencoder is shown below: The encoding part has 2 convolution layers (each followed by a max-pooling layer) and a fully connected layer. This part would encode an input ...

This notebook implements, in some sense, the simplest possible autoencoder: one that tries to reconstruct an arbitrary high-dimensional vector from a lower-dimensional internal representation.