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cs.LG2018
Approximating the Void: Learning Stochastic Channel Models from Observation with Variational Generative Adversarial Networks
Timothy J. O'Shea, Tamoghna Roy, Nathan West
Channel modeling is a critical topic when considering designing, learning, or evaluating the performance of any communications system. Most prior work in designing or learning new…
cs.LG2017★ 19 cited
Deep Architectures for Modulation Recognition
Nathan E West, Timothy J. O'Shea
We survey the latest advances in machine learning with deep neural networks by applying them to the task of radio modulation recognition. Results show that radio modulation recogni…