… channel coding scheme with novel neural structure and training algorithms. TurboAE learns
capacity-approaching code on various channels … discovery of codes for channels where a …

… jointly by training a DNN at each user and a DNN at the BS. In particular, we propose a novel
neural … By properly training the proposed neural network, we jointly optimize the downlink …

… In this paper, we propose a novel neural network structure for jointly … usually includes
source coding, channel coding, and … , channel estimation, equalization, demodulation, channel …

… Since the state-of-the-art recognition is achieved by applying deep neural networks (DNNs)
and it has recently been shown that channel codes and joint source-channel coding can …

… in order to form the neural basis that can … neuronal responses can be understood as an
emergent property of nonnegative sparse coding (NSC)—a form of efficient population coding …

… Moreover, we are able to perform joint compression and enhancement either at the
encoder or at the decoder side with no additional latency, which we demonstrate through …

… , that consists of an encoder, a non-trainable channel layer, and a decoder … encoder and
decoder essentially implement joint source-channel coding via lightweight convolutional neural …

… For the NTC examples above, we used neural networks with 4 fully connected (ie, non-…
The approximation capacity, ie, the capability of the neural network to approximate increasingly …

… of channel coding. We incorporate the recently proposed deep joint source-channel coding
(… at reducing the redundant complexity from neural networks. We evaluate our approach on a …

… joint source-channel coding methods to achieve end-to-end video transmission over wireless
channels… Furthermore, we compare our DVST with the emerging neural video compression …