The Autoencoder Based on Generalized Neo-Fuzzy Neuron and its Fast Learning for Deep Neural Networks

Abstract

In this paper the autoencoder based on the generalized neo-fuzzy neurons is proposed. Also its fast learning algorithm based on quadratic criterion was proposed. Such system can be used as part of deep learning systems. The proposed autoencoder is characterized by high learning speed and less number of tuned parameters in comparison with wellknown autoencoders of "bottle neck" type. The efficiency of proposed approach has been justified based on different benchmarks and real data sets.