Figure 1.

Architecture of a basic autoencoder. V (1,2…n), entire training data; X (1,2…n), set of training data; b_h, bias of hidden layer; b_x, bias of input layer; h (1,2…m), feature vector at hidden layer; xˆ, reconstruction of input x.