Non-catastrophicity in multidimensional convolutional coding

DOI10.1016/j.disc.2019.111789zbMath1468.94437OpenAlexW2999723644WikidataQ126357339 ScholiaQ126357339MaRDI QIDQ2305903

Vakhtang Lomadze

Publication date: 20 March 2020

Published in: Discrete Mathematics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.disc.2019.111789

zbMATH Keywords

moduleslinear systemspolynomialsconvolutional codesformal seriesnon-catastrophicity

Mathematics Subject Classification ID

Convolutional codes (94B10)

Cites Work

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• Input-state-output representations and constructions of finite support 2D convolutional codes
• Algebraic decoder of multidimensional convolutional code: Constructive algorithms for determining syndrome decoder and decoder matrix based on Gröbner basis
• Applications of algebraic topology. Graphs and networks. The Picard- Lefschetz theory and Feynman integrals
• On 2D finite support convolutional codes: An algebraic approach
• The predictable degree property and minimality in multidimensional convolutional coding
• Local cohomology. A seminar given by A. Grothendieck, Harvard University, Fall 1961. Notes by R. Hartshorne
• The PBH test for multidimensional LTID systems
• On behaviors and convolutional codes
• Algebraic aspects of two-dimensional convolutional codes
• Multidimensional Convolutional Codes
• Inverses of Linear Sequential Circuits

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