  In this work we compare the capacity and achievable rate of uncoded faster
than Nyquist (FTN) signalling in the frequency domain, also referred to as
spectrally efficient FDM (SEFDM). We propose a deep residual convolutional
neural network detector for SEFDM signals in additive white Gaussian noise
channels, that allows to approach the Mazo limit in systems with up to 60
subcarriers. Notably, the deep detectors achieve a loss less than 0.4-0.7 dB
for uncoded QPSK SEFDM systems of 12 to 60 subcarriers at a 15% spectral
compression.
