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Deep Learning for the Gaussian Wiretap Channel
[article]
2019
arXiv
pre-print
End-to-end learning of communication systems with neural networks and particularly autoencoders is an emerging research direction which gained popularity in the last year. In this approach, neural networks learn to simultaneously optimize encoding and decoding functions to establish reliable message transmission. In this paper, this line of thinking is extended to communication scenarios in which an eavesdropper must further be kept ignorant about the communication. The secrecy of the
arXiv:1810.12655v2
fatcat:6unu4li36feifidh62swqpg2ra