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  2. Suffix array - Wikipedia

    en.wikipedia.org/wiki/Suffix_array

    Suffix array. In computer science, a suffix array is a sorted array of all suffixes of a string. It is a data structure used in, among others, full-text indices, data-compression algorithms, and the field of bibliometrics . Suffix arrays were introduced by Manber & Myers (1990) as a simple, space efficient alternative to suffix trees.

  3. Generator matrix - Wikipedia

    en.wikipedia.org/wiki/Generator_matrix

    A generator matrix for a linear -code has format , where n is the length of a codeword, k is the number of information bits (the dimension of C as a vector subspace), d is the minimum distance of the code, and q is size of the finite field, that is, the number of symbols in the alphabet (thus, q = 2 indicates a binary code, etc.).

  4. Hamming (7,4) - Wikipedia

    en.wikipedia.org/wiki/Hamming(7,4)

    Hamming codes can be computed in linear algebra terms through matrices because Hamming codes are linear codes. For the purposes of Hamming codes, two Hamming matrices can be defined: the code generator matrix G and the parity-check matrix H :

  5. Ternary Golay code - Wikipedia

    en.wikipedia.org/wiki/Ternary_Golay_code

    A generator matrix for the extended ternary Golay code is The corresponding parity check matrix for this generator matrix is , where denotes the transpose of the matrix.

  6. Reed–Muller code - Wikipedia

    en.wikipedia.org/wiki/Reed–Muller_code

    Reed–Muller codes are linear block codes that are locally testable, locally decodable, and list decodable. These properties make them particularly useful in the design of probabilistically checkable proofs . Traditional Reed–Muller codes are binary codes, which means that messages and codewords are binary strings.

  7. Data Matrix - Wikipedia

    en.wikipedia.org/wiki/Data_Matrix

    A Data Matrix is a two-dimensional code consisting of black and white "cells" or dots arranged in either a square or rectangular pattern, also known as a matrix. The information to be encoded can be text or numeric data. Usual data size is from a few bytes up to 1556 bytes. The length of the encoded data depends on the number of cells in the ...

  8. Levenshtein distance - Wikipedia

    en.wikipedia.org/wiki/Levenshtein_distance

    Levenshtein distance. In information theory, linguistics, and computer science, the Levenshtein distance is a string metric for measuring the difference between two sequences. The Levenshtein distance between two words is the minimum number of single-character edits (insertions, deletions or substitutions) required to change one word into the ...

  9. Hamming distance - Wikipedia

    en.wikipedia.org/wiki/Hamming_distance

    In information theory, the Hamming distance between two strings or vectors of equal length is the number of positions at which the corresponding symbols are different. In other words, it measures the minimum number of substitutions required to change one string into the other, or equivalently, the minimum number of errors that could have ...