Innovative Variational AutoEncoder for an End-to-End Communication System

Innovative Variational AutoEncoder for an End-to-End Communication System

Powered by deep learning (DL), autoencoders (AE) end-to-end (E2E) communication systems have been developed to merge all physical layer blocks in traditional communication systems and have achieved great success. In this paper, a new probabilistic model, based on the variational autoencoders (VAE),...

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Bibliographic Details
Main Authors: Mohamad A. Alawad, Mutasem Q. Hamdan, Khairi A. Hamdi
Format: Article
Language:English
Published: IEEE 2023-01-01
Series:IEEE Access
Subjects:
Variational autoencoder
machine learning
auto-encoder
Hamming code
latent random variable
probabilistic models
Online Access:https://ieeexplore.ieee.org/document/9964187/

Internet

https://ieeexplore.ieee.org/document/9964187/

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