6 datasets found

The dataset used in this paper is a collection of binary bits, turbo encoded and decoded using the proposed RNN architecture.

The dataset used in this paper is a simulation framework for turbo encoding and decoding operations. It consists of four autoencoding problems: one for encoding and three for...

The dataset used in the paper is a collection of modulated codewords and their corresponding noisy versions, used for training and testing the friendly attack algorithm.

The dataset used in the paper is a turbo encoder with two recursive systematic convolutional (RSC) encoders, and a finite-memory channel with memory length L = 3.

The dataset used in the paper is the AWGN channel with noisy feedback, where the terminals send and receive signals over a pair of independent AWGN channels.

The dataset used in this paper is a serial Turbo Autoencoder (TurboAE) with Gaussian priors (TGP) for component training.