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  2. Shannon–Fano–Elias coding - Wikipedia

    en.wikipedia.org/wiki/ShannonFanoElias_coding

    Shannon–FanoElias coding produces a binary prefix code, allowing for direct decoding. Let bcode(x) be the rational number formed by adding a decimal point before a binary code. For example, if code(C) = 1010 then bcode(C) = 0.1010. For all x, if no y exists such that

  3. Elias coding - Wikipedia

    en.wikipedia.org/wiki/Elias_coding

    Elias coding is a term used for one of two types of lossless coding schemes used in digital communications: Shannon–FanoElias coding, a precursor to arithmetic coding, in which probabilities are used to determine codewords; Universal coding using one of Elias' three universal codes, each with predetermined codewords: Elias delta coding

  4. Shannon–Fano coding - Wikipedia

    en.wikipedia.org/wiki/ShannonFano_coding

    Unfortunately, Shannon–Fano coding does not always produce optimal prefix codes; the set of probabilities {0.35, 0.17, 0.17, 0.16, 0.15} is an example of one that will be assigned non-optimal codes by Shannon–Fano coding. Fano's version of Shannon–Fano coding is used in the IMPLODE compression method, which is part of the ZIP file format ...

  5. Category:Data compression - Wikipedia

    en.wikipedia.org/wiki/Category:Data_compression

    Download as PDF; Printable version; ... Data compression software (6 C, 28 P) F. Compression file systems ... Shannon–FanoElias coding;

  6. Shannon coding - Wikipedia

    en.wikipedia.org/wiki/Shannon_coding

    In the field of data compression, Shannon coding, named after its creator, Claude Shannon, is a lossless data compression technique for constructing a prefix code based on a set of symbols and their probabilities (estimated or measured).

  7. Prefix code - Wikipedia

    en.wikipedia.org/wiki/Prefix_code

    For example, a code with code {9, 55} has the prefix property; a code consisting of {9, 5, 59, 55} does not, because "5" is a prefix of "59" and also of "55". A prefix code is a uniquely decodable code : given a complete and accurate sequence, a receiver can identify each word without requiring a special marker between words.

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  9. Entropy coding - Wikipedia

    en.wikipedia.org/wiki/Entropy_coding

    More precisely, the source coding theorem states that for any source distribution, the expected code length satisfies ⁡ [(())] ⁡ [⁡ (())], where is the number of symbols in a code word, is the coding function, is the number of symbols used to make output codes and is the probability of the source symbol. An entropy coding attempts to ...