code (coding theory)

In statistics and coding theory, a Hamming space (named after American mathematician Richard Hamming) is usually the set of all $2^N$ binary strings of length ''N''. It is used in the theory of coding signals and transmission.

More generally, a Hamming space can be defined over any alphabet (set) ''Q'' as the set of words of a fixed length ''N'' with letters from ''Q''.Cohen et al., ''Covering Codes'', p. 15 If ''Q'' is a finite field, then a Hamming space over ''Q'' is an ''N''-dimensional vector space over ''Q''. In the typical, binary case, the field is thus GF(2) (also denoted by Z₂).

In coding theory, if ''Q'' has ''q'' elements, then any subset ''C'' (usually assumed of cardinality at least two) of the ''N''-dimensional Hamming space over ''Q'' is called a q-ary code of length N; the elements of ''C'' are called codewords. In the case where ''C'' is a linear subspace of its Hamming space, it is called a linear code. A typical example of linear code is the Hamming code. Codes defined via a Hamming space necessarily have the same length for every codeword, so they are called block codes when it is necessary to distinguish them from variable-length codes that are defined by unique factorization on a monoid.

The Hamming distance endows a Hamming space with a metric, which is essential in defining basic notions of coding theory such as error detecting and error correcting codes.

Hamming spaces over non-field alphabets have also been considered, especially over finite rings (most notably over Z₄) giving rise to modules instead of vector spaces and ring-linear codes (identified with submodules) instead of linear codes. The typical metric used in this case the Lee distance. There exist a Gray isometry between $\mathbb_2^$ (i.e. GF(2^2m)) with the Hamming distance and $\mathbb_4^m$ (also denoted as GR(4,m)) with the Lee distance.

References

Coding theory
Linear algebra

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