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Machine Learning for Channel Coding: A Paradigm Shift from FEC Codes
Kayode A. Olaniyi
,
Reolyn Heymann
,
Theo G. Swart
Electrical and Electronic Engineering Science
University of Johannesburg
Research output
:
Contribution to journal
›
Article
›
peer-review
6
Citations (Scopus)
Overview
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Computer Science
Machine Learning
100%
Channel Coding
100%
Error Correction Code
100%
Forward Error Correction
100%
Paradigm Shift
100%
Channel Estimation
50%
Research Problem
25%
Information Technology
25%
Neural Network Architecture
25%
Deep Neural Network
25%
low-density parity-check code
25%
Open Research
25%
Technology Design
25%
Reliable Communication
25%
Engineering
Correction Code
100%
Forward Error-Correction
100%
Channel Coding
100%
Communication System
50%
Channel Estimation
50%
Channel Code
50%
Neural Network Architecture
25%
Information Technology
25%
Parity Check Code
25%
Reliable Communication
25%
Deep Neural Network
25%
Keyphrases
Optimal Channels
50%
Performance Flexibility
25%
Turbo
25%
Communication Algorithms
25%
Capacity-approaching
25%
Neuroscience
Neural Network
100%