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  2. Redundancy (information theory) - Wikipedia

    en.wikipedia.org/wiki/Redundancy_(information...

    Redundancy of compressed data refers to the difference between the expected compressed data length of messages () (or expected data rate () /) and the entropy (or entropy rate ). (Here we assume the data is ergodic and stationary , e.g., a memoryless source.)

  3. Don't repeat yourself - Wikipedia

    en.wikipedia.org/wiki/Don't_repeat_yourself

    "Don't repeat yourself" (DRY), also known as "duplication is evil", is a principle of software development aimed at reducing repetition of information which is likely to change, replacing it with abstractions that are less likely to change, or using data normalization which avoids redundancy in the first place.

  4. Fourier–Motzkin elimination - Wikipedia

    en.wikipedia.org/wiki/Fourier–Motzkin_elimination

    Since all the inequalities are in the same form (all less-than or all greater-than), we can examine the coefficient signs for each variable. Eliminating x would yield 2*2 = 4 inequalities on the remaining variables, and so would eliminating y. Eliminating z would yield only 3*1 = 3 inequalities so we use that instead.

  5. Error correction code - Wikipedia

    en.wikipedia.org/wiki/Error_correction_code

    A redundant bit may be a complicated function of many original information bits. The original information may or may not appear literally in the encoded output; codes that include the unmodified input in the output are systematic , while those that do not are non-systematic .

  6. Information theory - Wikipedia

    en.wikipedia.org/wiki/Information_theory

    The BSC has a capacity of 1 − H b (p) bits per channel use, where H b is the binary entropy function to the base-2 logarithm: A binary erasure channel (BEC) with erasure probability p is a binary input, ternary output channel. The possible channel outputs are 0, 1, and a third symbol 'e' called an erasure.

  7. Reed–Solomon error correction - Wikipedia

    en.wikipedia.org/wiki/Reed–Solomon_error...

    Ie for DM is 301 % k is the size of the message % n is the total size (k+redundant) % Example: msg = uint8('Test') % enc_msg = rsEncoder(msg, 8, 301, 12, numel(msg)); % Get the alpha alpha = gf (2, m, prim_poly); % Get the Reed-Solomon generating polynomial g(x) g_x = genpoly (k, n, alpha); % Multiply the information by X^(n-k), or just pad ...

  8. Reliability block diagram - Wikipedia

    en.wikipedia.org/wiki/Reliability_block_diagram

    RBDs will indicate the type of redundancy in the parallel path. [1] For example, a group of parallel blocks could require two out of three components to succeed for the system to succeed. By contrast, any failure along a series path causes the entire series path to fail. [2] [3]

  9. Knuth's Algorithm X - Wikipedia

    en.wikipedia.org/wiki/Knuth's_Algorithm_X

    There are no more selected rows at level 2, thus the algorithm moves to the next branch at level 1… There are no more selected rows at level 1, thus the algorithm moves to the next branch at level 0… There are no branches at level 0, thus the algorithm terminates. In summary, the algorithm determines there is only one exact cover: S * = {B ...

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