Skip to Main content Skip to Navigation
Conference papers

Embedding Distances into the Hamming Cube

Abstract : In Coding Theory, two different decision criteria types are mostly used: a maximal likelihood (relative to a probabilistic model of a channel) and a nearest neighbour criterion (relative to a distance model of the channel). In this work we present an algorithm that, given a maximal likelihood criterion, decides if there is a nearest neighbour criterion that matches it and, in this case, produces a metric that determines such a criterion. It is also shown that the Hamming metric is universal, in the sense that any metric, up to a decoding equivalence, can be isometrically embedded into a hypercube with the Hamming metric.
Document type :
Conference papers
Complete list of metadata

Cited literature [5 references]  Display  Hide  Download
Contributor : Jean-Pierre Tillich Connect in order to contact the contributor
Submitted on : Friday, February 19, 2016 - 2:19:48 PM
Last modification on : Friday, August 5, 2022 - 11:41:00 AM
Long-term archiving on: : Friday, May 20, 2016 - 11:31:29 AM


Files produced by the author(s)


  • HAL Id : hal-01276469, version 1



Rafael Gregorio Lucas d'Oliveira, Marcelo Firer. Embedding Distances into the Hamming Cube. The 9th International Workshop on Coding and Cryptography 2015 WCC2015, Anne Canteaut, Gaëtan Leurent, Maria Naya-Plasencia, Apr 2015, Paris, France. ⟨hal-01276469⟩



Record views


Files downloads