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  2. Channel capacity - Wikipedia

    en.wikipedia.org/wiki/Channel_capacity

    To determine the channel capacity, it is necessary to find the capacity-achieving distribution () and evaluate the mutual information (;). Research has mostly focused on studying additive noise channels under certain power constraints and noise distributions, as analytical methods are not feasible in the majority of other scenarios.

  3. Noisy-channel coding theorem - Wikipedia

    en.wikipedia.org/wiki/Noisy-channel_coding_theorem

    The channel capacity can be calculated from the physical properties of a channel; for a band-limited channel with Gaussian noise, using the Shannon–Hartley theorem. Simple schemes such as "send the message 3 times and use a best 2 out of 3 voting scheme if the copies differ" are inefficient error-correction methods, unable to asymptotically ...

  4. 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.

  5. List of Cambridge International Examinations Advanced Level ...

    en.wikipedia.org/wiki/List_of_Cambridge...

    Notes CIE 8001: General Paper: AS Level only CIE 8004: General Paper: AS Level only CIE 8024 Nepal Studies: AS Level only [1] CIE 8041: Divinity: AS Level only CIE 8053: Islamic Studies: AS Level only CIE 8058: Hinduism: AS Level only CIE 8274: Language and Literature in English (US) available in the US only under the BES pilot; AS Level only ...

  6. Shannon–Hartley theorem - Wikipedia

    en.wikipedia.org/wiki/Shannon–Hartley_theorem

    Some authors refer to it as a capacity. But such an errorless channel is an idealization, and if M is chosen small enough to make the noisy channel nearly errorless, the result is necessarily less than the Shannon capacity of the noisy channel of bandwidth , which is the Hartley–Shannon result that followed later.

  7. Coding theory - Wikipedia

    en.wikipedia.org/wiki/Coding_theory

    the mutual information, and the channel capacity of a noisy channel, including the promise of perfect loss-free communication given by the noisy-channel coding theorem; the practical result of the Shannon–Hartley law for the channel capacity of a Gaussian channel; and of course; the bit - a new way of seeing the most fundamental unit of ...

  8. List of Cambridge International Examinations Ordinary Level ...

    en.wikipedia.org/wiki/List_of_Cambridge...

    Cannot be combined with syllabuses 0452 & 0614 , 4345, 7092 & 7175 (O Level).The Cambridge O Level Principles of Accounts 7110 syllabus has been revised and now has a new title and code: Cambridge O Level Accounting 7707. The last examination series for Cambridge O Level Principles of Accounts 7110 will be November 2019. [4] link: CIE 7115

  9. Blahut–Arimoto algorithm - Wikipedia

    en.wikipedia.org/wiki/Blahut–Arimoto_algorithm

    For the case of channel capacity, the algorithm was independently invented by Suguru Arimoto [1] and Richard Blahut. [2] In addition, Blahut's treatment gives algorithms for computing rate distortion and generalized capacity with input contraints (i.e. the capacity-cost function, analogous to rate-distortion).