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 Generalized column distances for convolutional codes
Please use this identifier to cite or link to this item http://hdl.handle.net/10773/18231

title: Generalized column distances for convolutional codes
authors: Cardel, Sara D.
Firer, Marcelo
Napp, Diego
keywords: convolutional codes
issue date: 26-Jun-2017
publisher: IEEE
abstract: In this work, we adapt the notion of generalized Hamming weight of block codes to introduce the novel concept of generalized column distances for convolutional codes. This can be considered as an extension of the work done in [18] on the generalized Hamming weights for free distance of convolutional codes. We also introduce the concept of Almost-MDP and NearMDP convolutional code. The problem of constructing convolutional codes with design generalized column distances remains an interesting open problem that requires further research.
URI: http://hdl.handle.net/10773/18231
publisher version/DOI: https://isit2017.org/
source: ISIT 2017: The IEEE International Symposium on Information Theory
appears in collectionsCIDMA - Comunicações

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