Optimisation of reinforcement learning-based decoding strategies for binary linear codes

Linear codes are a class of error-correcting codes, whereby any linear combination of two codewords always results in another codeword. In general, they are defined over a finite field, and have broad applications in the fields of communications and information systems. The present work surveys the...

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Main Author: Ang, Rosamund Pei Yin
Other Authors: Frederique Elise Oggier
Format: Final Year Project
Language:English
Published: Nanyang Technological University 2022
Subjects:
Online Access:https://hdl.handle.net/10356/156951
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1569512023-02-28T23:15:43Z Optimisation of reinforcement learning-based decoding strategies for binary linear codes Ang, Rosamund Pei Yin Frederique Elise Oggier School of Physical and Mathematical Sciences Adam Chai Kian Ming Frederique@ntu.edu.sg, ckianmin@dso.org.sg Science::Mathematics Linear codes are a class of error-correcting codes, whereby any linear combination of two codewords always results in another codeword. In general, they are defined over a finite field, and have broad applications in the fields of communications and information systems. The present work surveys the construction and decoding methods for binary linear codes, and approaches the decoding of such linear codes as a reinforcement learning (RL) problem. The present work also presents a general theoretical RL-based framework for the decoding of binary linear codes over a binary symmetric channel (BSC). Bachelor of Science in Mathematical Sciences 2022-04-30T05:37:51Z 2022-04-30T05:37:51Z 2022 Final Year Project (FYP) Ang, R. P. Y. (2022). Optimisation of reinforcement learning-based decoding strategies for binary linear codes. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/156951 https://hdl.handle.net/10356/156951 en application/pdf Nanyang Technological University
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Science::Mathematics
spellingShingle Science::Mathematics
Ang, Rosamund Pei Yin
Optimisation of reinforcement learning-based decoding strategies for binary linear codes
description Linear codes are a class of error-correcting codes, whereby any linear combination of two codewords always results in another codeword. In general, they are defined over a finite field, and have broad applications in the fields of communications and information systems. The present work surveys the construction and decoding methods for binary linear codes, and approaches the decoding of such linear codes as a reinforcement learning (RL) problem. The present work also presents a general theoretical RL-based framework for the decoding of binary linear codes over a binary symmetric channel (BSC).
author2 Frederique Elise Oggier
author_facet Frederique Elise Oggier
Ang, Rosamund Pei Yin
format Final Year Project
author Ang, Rosamund Pei Yin
author_sort Ang, Rosamund Pei Yin
title Optimisation of reinforcement learning-based decoding strategies for binary linear codes
title_short Optimisation of reinforcement learning-based decoding strategies for binary linear codes
title_full Optimisation of reinforcement learning-based decoding strategies for binary linear codes
title_fullStr Optimisation of reinforcement learning-based decoding strategies for binary linear codes
title_full_unstemmed Optimisation of reinforcement learning-based decoding strategies for binary linear codes
title_sort optimisation of reinforcement learning-based decoding strategies for binary linear codes
publisher Nanyang Technological University
publishDate 2022
url https://hdl.handle.net/10356/156951
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