Robust Deep Neural Network Using Fuzzy Denoising Autoencoder

Deep neural network (DNN) has been applied in many fields and achieved great successes. However, DNN suffers from poor robustness for uncertainties because of its characteristic of the deterministic representation. To overcome this problem, a novel robust DNN (RDNN) is designed in this paper. First, a fuzzy denoising autoencoder (FDA) is developed to replace the general base-building unit in DNN. Then, the proposed RDNN is able to extract the...