Hamming distance


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hamming distance

[′ham·iŋ ‚dis·təns]
(computer science)

Hamming distance

(data)
The minimum number of bits that must be changed in order to convert one bit string into another.

Named after the mathematician Richard Hamming.

References in periodicals archive ?
Hamming distance between two keys is used to evaluate the closeness between the generated keys.
The Hamming distance of two iris codes before and after encryption remain the same, as long as the keys used to encrypt them are identical.
The network must select the sample with minimum Hamming distance to unknown input signal resulting in activation of only one network output which corresponds to this sample (Carlin et al.
For q = 2, 3, the Euclidean square distance bound obtained in Theorem 3.1 coincides with the corresponding bound for the Hamming distance codes [11, Theorem 4.1] and the Lee distance codes [3, Theorem 3] using the fact that the Euclidean square distance reduces to the Hamming and Lee distance for binary and ternary cases.
For a code matrix M = ([m.sub.ij])kxL, the minimum Hamming distance between any pair of rows of the code matrix M is called the minimum Hamming distance of the code matrix M.
The Hamming distance (or simply distance) H(P(z),Q(z)) between two polynomials P(z) = [SIGMA][p.sub.k][z.sup.k] and Q(z) = [SIGMA][q.sub.k][z.sup.k] is the number of coefficients for which [p.sub.k] [not equal to] [q.sub.k].
This way of doing is very similar to classification procedure in the Maxnet network, the unique difference is the use of semantic metrics instead of Hamming distance. This searching algorithm is very easily developable, but it is not the best solution because it sometimes only partially matches the keywords set in the query, even if data requested are entirely present in the system; for example, it can happen that a group of documents, when they unite their keywords labels, is closer to the target expressed in the query compared to the single document chosen with the best matching rule.
For the highest-ranked treatment, current resistance (CurrWt) and nearby mutation score (MutScor) are small, and only a weakly resistant mutant appears even out to Hamming distance three (3 Mut).
The non-binary indirect network (with fast finishing) will take fewer than [log.sub.2]N cycles to route packets, but distances are not given by the Hamming distance. However, to get the same number of stages, the non-binary indirect network uses larger switches than the composite network.
Here we use Hamming distance to measure the distantance between two TrNN.
Generally, LT13 consists of two stages: (1) Computing the encrypted Hamming distance [[d]] between x and y such that only Alice learns [[d]].
Motivated by PFLS [24] that is based on LVs and PFS, we define the notion of PFULS based on ULVs and PFS and present operational laws, score function, accuracy function, and normalized Hamming distance of PFULVs.