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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 .
Encoding, in semiotics, is the process of creating a message for transmission by an addresser to an addressee. The complementary process – interpreting a message received from an addresser – is called decoding .
Production – This is where the encoding, the construction of a message begins. Production process has its own "discursive" aspect, as it is also framed by meanings and ideas; by drawing upon society's dominant ideologies, the creator of the message is feeding off of society's beliefs, and values.
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.
As digital sound became the standard of sound reproduction in the 21st century, 35 and 70-mm films have increasingly included a digital version of the soundtrack on the edges of the film strip. Most films continue to be processed with both digital and analog soundtracks so they may be read by any projection systems in a movie theater.
In hardware, audio codec refers to a single device that encodes analog audio as digital signals and decodes digital back into analog. In other words, it contains both an analog-to-digital converter (ADC) and digital-to-analog converter (DAC) running off the same clock signal. This is used in sound cards that support both audio in and out, for ...
A lossless audio coding format reduces the total data needed to represent a sound but can be de-coded to its original, uncompressed form. A lossy audio coding format additionally reduces the bit resolution of the sound on top of compression, which results in far less data at the cost of irretrievably lost information.