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In information theory, Shannon–Fano–Elias coding is a precursor to arithmetic coding, in which probabilities are used to determine codewords. [1] It is named for Claude Shannon , Robert Fano , and Peter Elias .
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).
Fano's method usually produces encoding with shorter expected lengths than Shannon's method. However, Shannon's method is easier to analyse theoretically. Shannon–Fano coding should not be confused with Shannon–Fano–Elias coding (also known as Elias coding), the precursor to arithmetic coding.
Elias coding is a term used for one of two types of lossless coding schemes used in digital communications: . Shannon–Fano–Elias coding, a precursor to arithmetic coding, in which probabilities are used to determine codewords
The term encoding-decoding model is used for any model that includes the phases of encoding and decoding in its description of communication. Such models stress that to send information, a code is necessary. A code is a sign system used to express ideas and interpret messages. Encoding-decoding models are sometimes contrasted with inferential ...
Thus, encoding/decoding is the translation needed for a message to be easily understood. When you decode a message, you extract the meaning of that message in ways to simplify it. Decoding has both verbal and non-verbal forms of communication: Decoding behavior without using words, such as displays of non-verbal communication.
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Using the unit shannon is an explicit reference to a quantity of information content, information entropy or channel capacity, and is not restricted to binary data, [2] whereas bits can as well refer to the number of binary symbols involved, as is the term used in fields such as data processing.