This article explores some of the most influential deep learning architectures: Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), Generative Adversarial Networks (GANs), ...

Recurrent neural networks, or RNNs, ... They use a dense feedforward network as a sub-neural net inside the encoder and decoder components. They also demand considerable computing power.

However, in contrast to conventional communication systems, the design of end-to-end communication systems based on deep learning networks adopts a holistic approach where both the transmitter and ...

Abstract: In this article, a stochastic recurrent encoder decoder neural network (SREDNN), which considers latent random variables in its recurrent structures, is developed for the first time for the ...