activity
20192021
most citedMeta-ViterbiNet: Online Meta-Learned Viterbi Equalization for Non-Stationary Channels

2 citations · 2 across the 1 of their papers we have counts for

collaborators

5 papers

cs.IT20212 cited

Meta-ViterbiNet: Online Meta-Learned Viterbi Equalization for Non-Stationary Channels

Tomer Raviv, Sangwoo Park, Nir Shlezinger +3

Deep neural networks (DNNs) based digital receivers can potentially operate in complex environments. However, the dynamic nature of communication channels implies that in some scen…

cs.IT2020

Deep Ensemble of Weighted Viterbi Decoders for Tail-Biting Convolutional Codes

Tomer Raviv, Asaf Schwartz, Yair Be'ery

Tail-biting convolutional codes extend the classical zero-termination convolutional codes: Both encoding schemes force the equality of start and end states, but under the tail-biti…

cs.IT2020

perm2vec: Graph Permutation Selection for Decoding of Error Correction Codes using Self-Attention

Nir Raviv, Avi Caciularu, Tomer Raviv +2

Error correction codes are an integral part of communication applications, boosting the reliability of transmission. The optimal decoding of transmitted codewords is the maximum li…

cs.IT2020

Data-Driven Ensembles for Deep and Hard-Decision Hybrid Decoding

Tomer Raviv, Nir Raviv, Yair Be'ery

Ensemble models are widely used to solve complex tasks by their decomposition into multiple simpler tasks, each one solved locally by a single member of the ensemble. Decoding of e…

cs.IT2019

Active Deep Decoding of Linear Codes

Ishay Be'ery, Nir Raviv, Tomer Raviv +1

High quality data is essential in deep learning to train a robust model. While in other fields data is sparse and costly to collect, in error decoding it is free to query and label…