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A modern-day example of the dominant-hegemonic code is described by communication scholar Garrett Castleberry in his article "Understanding Stuart Hall's 'Encoding/Decoding' Through AMC's Breaking Bad". Castleberry argues that there is a dominant-hegemonic "position held by the entertainment industry that illegal drug side-effects cause less ...
The term algebraic coding theory denotes the sub-field of coding theory where the properties of codes are expressed in algebraic terms and then further researched. [ citation needed ] Algebraic coding theory is basically divided into two major types of codes: [ citation needed ]
Neural coding (or neural representation) is a neuroscience field concerned with characterising the hypothetical relationship between the stimulus and the neuronal responses, and the relationship among the electrical activities of the neurons in the ensemble.
During the encoding of a frame, the input data bits (D) are repeated and distributed to a set of constituent encoders. The constituent encoders are typically accumulators and each accumulator is used to generate a parity symbol. A single copy of the original data (S 0,K-1) is transmitted with the parity bits (P) to make up the code symbols. The ...
Convolutional code with any code rate can be designed based on polynomial selection; [15] however, in practice, a puncturing procedure is often used to achieve the required code rate. Puncturing is a technique used to make a m/n rate code from a "basic" low-rate (e.g., 1/n) code. It is achieved by deleting of some bits in the encoder output.
Encoding is still relatively new and unexplored but the origins of encoding date back to age-old philosophers such as Aristotle and Plato. A major figure in the history of encoding is Hermann Ebbinghaus (1850–1909). Ebbinghaus was a pioneer in the field of memory research.
In information theory, an entropy coding (or entropy encoding) is any lossless data compression method that attempts to approach the lower bound declared by Shannon's source coding theorem, which states that any lossless data compression method must have an expected code length greater than or equal to the entropy of the source.
Such an approach allows simpler and faster encoding/decoding than arithmetic coding or even Huffman coding, since the latter requires a table lookups. In the {0.95, 0.05} example, a Golomb-Rice code with a four-bit remainder achieves a compression ratio of 71.1 % {\displaystyle 71.1\%} , far closer to optimum than using three-bit blocks.