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  2. Recall (memory) - Wikipedia

    en.wikipedia.org/wiki/Recall_(memory)

    The theory of encoding specificity finds similarities between the process of recognition and that of recall. The encoding specificity principle states that memory utilizes information from the memory trace, or the situation in which it was learned, and from the environment in which it is retrieved. In other words, memory is improved when ...

  3. History of information theory - Wikipedia

    en.wikipedia.org/wiki/History_of_information_theory

    The expected change in the weight of evidence is equivalent to what was later called the Kullback discrimination information. But underlying this notion was still the idea of equal a-priori probabilities, rather than the information content of events of unequal probability; nor yet any underlying picture of questions regarding the communication ...

  4. Encoding specificity principle - Wikipedia

    en.wikipedia.org/wiki/Encoding_specificity_principle

    The encoding specificity principle is the general principle that matching the encoding contexts of information at recall assists in the retrieval of episodic memories. It provides a framework for understanding how the conditions present while encoding information relate to memory and recall of that information.

  5. Encoding (memory) - Wikipedia

    en.wikipedia.org/wiki/Encoding_(memory)

    Semantic encoding is the processing and encoding of sensory input that has particular meaning or can be applied to a context. Various strategies can be applied such as chunking and mnemonics to aid in encoding, and in some cases, allow deep processing, and optimizing retrieval.

  6. Linear code - Wikipedia

    en.wikipedia.org/wiki/Linear_code

    The weight of a codeword is the number of its elements that are nonzero and the distance between two codewords is the Hamming distance between them, that is, the number of elements in which they differ.

  7. Hamming weight - Wikipedia

    en.wikipedia.org/wiki/Hamming_weight

    In error-correcting coding, the minimum Hamming weight, commonly referred to as the minimum weight w min of a code is the weight of the lowest-weight non-zero code word. The weight w of a code word is the number of 1s in the word. For example, the word 11001010 has a weight of 4.

  8. Hadamard code - Wikipedia

    en.wikipedia.org/wiki/Hadamard_code

    Since the Walsh–Hadamard code is a linear code, the distance is equal to the minimum Hamming weight among all of its non-zero codewords. All non-zero codewords of the Walsh–Hadamard code have a Hamming weight of exactly by the following argument. Let {,} be a non-zero message. Then the following value is exactly equal to the fraction of ...

  9. Constant-weight code - Wikipedia

    en.wikipedia.org/wiki/Constant-weight_code

    The 3-wire lane encoding used in MIPI C-PHY can be considered a generalization of constant-weight code to ternary -- each wire transmits a ternary signal, and at any one instant one of the 3 wires is transmitting a low, one is transmitting a middle, and one is transmitting a high signal.