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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2022
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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 |
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Science::Mathematics Ang, Rosamund Pei Yin Optimisation of reinforcement learning-based decoding strategies for binary linear codes |
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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 |
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Nanyang Technological University |
publishDate |
2022 |
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https://hdl.handle.net/10356/156951 |
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1759856048278077440 |