429 citations · 939 across the 56 of their papers we have counts for
5 papers · 1 filter
Pruning and Quantizing Neural Belief Propagation Decoders
Andreas Buchberger, Christian Häger, Henry D. Pfister +2
We consider near maximum-likelihood (ML) decoding of short linear block codes. In particular, we propose a novel decoding approach based on neural belief propagation (NBP) decoding…
Learned Decimation for Neural Belief Propagation Decoders
Andreas Buchberger, Christian Häger, Henry D. Pfister +2
We introduce a two-stage decimation process to improve the performance of neural belief propagation (NBP), recently introduced by Nachmani et al., for short low-density parity-chec…
Experimental Investigation of Deep Learning for Digital Signal Processing in Short Reach Optical Fiber Communications
Boris Karanov, Mathieu Chagnon, Vahid Aref +4
We investigate methods for experimental performance enhancement of auto-encoders based on a recurrent neural network (RNN) for communication over dispersive nonlinear channels. In…
Optical Fiber Communication Systems Based on End-to-End Deep Learning
Boris Karanov, Mathieu Chagnon, Vahid Aref +3
We investigate end-to-end optimized optical transmission systems based on feedforward or bidirectional recurrent neural networks (BRNN) and deep learning. In particular, we report…
Pruning Neural Belief Propagation Decoders
Andreas Buchberger, Christian Häger, Henry D. Pfister +2
We consider near maximum-likelihood (ML) decoding of short linear block codes based on neural belief propagation (BP) decoding recently introduced by Nachmani et al.. While this me…