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Nonasymptotic Upper Bounds on Binary Single Deletion Codes via Mixed Integer Linear Programming

The size of the largest binary single deletion code has been unknown for more than 50 years. It is known that Varshamov–Tenengolts (VT) code is an optimum single deletion code for block length [Formula: see text]; however, only a few upper bounds of the size of single deletion code are proposed for...

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Autor principal: No, Albert
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7514547/
http://dx.doi.org/10.3390/e21121202
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author No, Albert
author_facet No, Albert
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description The size of the largest binary single deletion code has been unknown for more than 50 years. It is known that Varshamov–Tenengolts (VT) code is an optimum single deletion code for block length [Formula: see text]; however, only a few upper bounds of the size of single deletion code are proposed for larger n. We provide improved upper bounds using Mixed Integer Linear Programming (MILP) relaxation technique. Especially, we show the size of single deletion code is smaller than or equal to 173 when the block length n is 11. In the second half of the paper, we propose a conjecture that is equivalent to the long-lasting conjecture that “VT code is optimum for all n”. This equivalent formulation of the conjecture contains small sub-problems that can be numerically verified. We provide numerical results that support the conjecture.
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spelling pubmed-75145472020-11-09 Nonasymptotic Upper Bounds on Binary Single Deletion Codes via Mixed Integer Linear Programming No, Albert Entropy (Basel) Article The size of the largest binary single deletion code has been unknown for more than 50 years. It is known that Varshamov–Tenengolts (VT) code is an optimum single deletion code for block length [Formula: see text]; however, only a few upper bounds of the size of single deletion code are proposed for larger n. We provide improved upper bounds using Mixed Integer Linear Programming (MILP) relaxation technique. Especially, we show the size of single deletion code is smaller than or equal to 173 when the block length n is 11. In the second half of the paper, we propose a conjecture that is equivalent to the long-lasting conjecture that “VT code is optimum for all n”. This equivalent formulation of the conjecture contains small sub-problems that can be numerically verified. We provide numerical results that support the conjecture. MDPI 2019-12-06 /pmc/articles/PMC7514547/ http://dx.doi.org/10.3390/e21121202 Text en © 2019 by the author. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
No, Albert
Nonasymptotic Upper Bounds on Binary Single Deletion Codes via Mixed Integer Linear Programming
title Nonasymptotic Upper Bounds on Binary Single Deletion Codes via Mixed Integer Linear Programming
title_full Nonasymptotic Upper Bounds on Binary Single Deletion Codes via Mixed Integer Linear Programming
title_fullStr Nonasymptotic Upper Bounds on Binary Single Deletion Codes via Mixed Integer Linear Programming
title_full_unstemmed Nonasymptotic Upper Bounds on Binary Single Deletion Codes via Mixed Integer Linear Programming
title_short Nonasymptotic Upper Bounds on Binary Single Deletion Codes via Mixed Integer Linear Programming
title_sort nonasymptotic upper bounds on binary single deletion codes via mixed integer linear programming
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7514547/
http://dx.doi.org/10.3390/e21121202
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