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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. 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 ...

  4. 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

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    98 MB of free disk space; Download and install the latest Java Virtual Machine in Internet Explorer. 1. Go to www.java.com. 2. Click Free Java Download. 3. Click Agree and Start Free Download. 4. Click Run. Notes: If prompted by the User Account Control window, click Yes. If prompted by the Security Warning window, click Run. 5.

  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. 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 ...

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  9. Robert Fano - Wikipedia

    en.wikipedia.org/wiki/Robert_Fano

    Fano was known principally for his work on information theory. He developed Shannon–Fano coding [12] in collaboration with Claude Shannon, and derived the Fano inequality. He also invented the Fano algorithm and postulated the Fano metric. [13] In the early 1960s, Fano was involved in the development of time-sharing computers.

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