this paper to accurately and steadily diagnose rolling bearing faults. In this paper, we employ a … An autoencoder is a type of artificial neural network used to learn efficient data codings in an unsupervised manner. In this paper, a novel deep neural network is proposed for emotion classification using EEG systems, which combines the Convolutional Neural Network (CNN), Sparse Autoencoder (SAE), and Deep Neural Network (DNN) together. The sparse coding block has an architecture similar to an encoder part of k-sparse autoencoder [46]. The CSAE adds Gaussian stochastic unit into activation function to extract features of nonlinear data. sparse autoencoder. Note that p