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In computer science and information theory, a Huffman code is a particular type of optimal prefix code that is commonly used for lossless data compression.The process of finding or using such a code is Huffman coding, an algorithm developed by David A. Huffman while he was a Sc.D. student at MIT, and published in the 1952 paper "A Method for the Construction of Minimum-Redundancy Codes".
Code dates from 1968 available here: [11] 1983 BHCOAT Craig F. Bohren and Donald R. Huffman [1] Fortran: No specified but open source (public domain via [1]) "Mie solutions" (infinite series) to scattering, absorption and phase function of electromagnetic waves by a homogeneous concentring shells. 1997 BART [12] A. Quirantes [13] Fortran
An entropy coding attempts to approach this lower bound. Two of the most common entropy coding techniques are Huffman coding and arithmetic coding. [2] If the approximate entropy characteristics of a data stream are known in advance (especially for signal compression), a simpler static code may be useful.
To make the code a canonical Huffman code, the codes are renumbered. The bit lengths stay the same with the code book being sorted first by codeword length and secondly by alphabetical value of the letter: B = 0 A = 11 C = 101 D = 100 Each of the existing codes are replaced with a new one of the same length, using the following algorithm:
Huffman coding is a more sophisticated technique for constructing variable-length prefix codes. The Huffman coding algorithm takes as input the frequencies that the code words should have, and constructs a prefix code that minimizes the weighted average of the code word lengths. (This is closely related to minimizing the entropy.)
Many popular archivers like ARJ, RAR, ZOO, LHarc use LZSS rather than LZ77 as the primary compression algorithm; the encoding of literal characters and of length-distance pairs varies, with the most common option being Huffman coding. Most implementations stem from a public domain 1989 code by Haruhiko Okumura.
The package-merge algorithm is an O(nL)-time algorithm for finding an optimal length-limited Huffman code for a given distribution on a given alphabet of size n, where no code word is longer than L. It is a greedy algorithm, and a generalization of Huffman's original algorithm.
Unlike variable-length codes, which include Huffman and Lempel–Ziv coding, Tunstall coding is a code which maps source symbols to a fixed number of bits. [2]Both Tunstall codes and Lempel–Ziv codes represent variable-length words by fixed-length codes.