571 citations · 929 across the 39 of their papers we have counts for
10 papers · 1 filter
Toward Optimal ANC: Establishing Mutual Information Lower Bound
François Derrida, Shahar Lutati, Eliya Nachmani
Active Noise Cancellation (ANC) algorithms aim to suppress unwanted acoustic disturbances by generating anti-noise signals that destructively interfere with the original noise in r…
Hybrid Mamba-Transformer Decoder for Error-Correcting Codes
Shy-el Cohen, Yoni Choukroun, Eliya Nachmani
We introduce a novel deep learning method for decoding error correction codes based on the Mamba architecture, enhanced with Transformer layers. Our approach proposes a hybrid deco…
Neural Decoding with Optimization of Node Activations
Eliya Nachmani, Yair Be'ery
The problem of maximum likelihood decoding with a neural decoder for error-correcting code is considered. It is shown that the neural decoder can be improved with two novel loss te…
Autoregressive Belief Propagation for Decoding Block Codes
Eliya Nachmani, Lior Wolf
We revisit recent methods that employ graph neural networks for decoding error correcting codes and employ messages that are computed in an autoregressive manner. The outgoing mess…
A Gated Hypernet Decoder for Polar Codes
Eliya Nachmani, Lior Wolf
Hypernetworks were recently shown to improve the performance of message passing algorithms for decoding error correcting codes. In this work, we demonstrate how hypernetworks can b…
Hyper-Graph-Network Decoders for Block Codes
Eliya Nachmani, Lior Wolf
Neural decoders were shown to outperform classical message passing techniques for short BCH codes. In this work, we extend these results to much larger families of algebraic block…
Near Maximum Likelihood Decoding with Deep Learning
Eliya Nachmani, Yaron Bachar, Elad Marciano +2
A novel and efficient neural decoder algorithm is proposed. The proposed decoder is based on the neural Belief Propagation algorithm and the Automorphism Group. By combining neural…
Deep Learning Methods for Improved Decoding of Linear Codes
Eliya Nachmani, Elad Marciano, Loren Lugosch +3
The problem of low complexity, close to optimal, channel decoding of linear codes with short to moderate block length is considered. It is shown that deep learning methods can be u…
RNN Decoding of Linear Block Codes
Eliya Nachmani, Elad Marciano, David Burshtein +1
Designing a practical, low complexity, close to optimal, channel decoder for powerful algebraic codes with short to moderate block length is an open research problem. Recently it h…
Learning to Decode Linear Codes Using Deep Learning
Eliya Nachmani, Yair Beery, David Burshtein
A novel deep learning method for improving the belief propagation algorithm is proposed. The method generalizes the standard belief propagation algorithm by assigning weights to th…