… for decoding high density parity check codes (HDPCs). Other methods for using deep learning
to decode error … In this work we combine the deep recurrent neural decoder of [10] with …

… This concept was shown to be similar to maximum likelihood decoding (MLD) of linear
block error-correcting codes (ECCs) [6]: an erroneous codeword will converge to the nearest …

… likelihood decoder [15]. In this work we focus on HDPC codes and demonstrate how the
BP algorithm can be improved. The naive approach to the problem is to assume a neural …

… channel decoding problem (ie, the maximum likelihood decoding … decoding methods with
affordable computational complexities. This work applies the latest advances in deep learning …

… of the decoding hypersphere is learned by a deep neural … is very close to the optimal maximum
likelihood decoding (MLD) over a … , compared to existing sphere decoding variants, is sig…

… an application of deep learning methods to the problem of low complexity channel decoding.
A well-… Scholl, “Efficient maximum-likelihood decoding of linear block codes on binary mem- …

… /decoding of the complex modulations/codes that approach the Shannon capacity. Theoretically,
the maximum likelihood … 2^k)$ demodulation/decoding complexity with $k$ denoting the …

… We also implement the maximum likelihood (ML) decoding of CS codes, where the
codeword with the closest Euclidean distance to the received noisy version of the codeword is …

… In our context of deep learning, its potential lies in the … Our approach in this paper extends
syndrome decoding to include … propose two deep neural network architectures for decoding of …

… The above deep learning Polar cod decoding papers, … to address is deep learning based
Polar code decoding in the … reliability, SC decoding is to judge the log likelihood ratio (LLR) …