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  2. 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 ...

  3. Channel capacity - Wikipedia

    en.wikipedia.org/wiki/Channel_capacity

    Information theory, developed by Claude E. Shannon in 1948, defines the notion of channel capacity and provides a mathematical model by which it may be computed. The key result states that the capacity of the channel, as defined above, is given by the maximum of the mutual information between the input and output of the channel, where the ...

  4. Shannon–Hartley theorem - Wikipedia

    en.wikipedia.org/wiki/Shannon–Hartley_theorem

    It is an application of the noisy-channel coding theorem to the archetypal case of a continuous-time analog communications channel subject to Gaussian noise. The theorem establishes Shannon's channel capacity for such a communication link, a bound on the maximum amount of error-free information per time unit that can be transmitted with a ...

  5. Information theory - Wikipedia

    en.wikipedia.org/wiki/Information_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; as well as; the bit—a new way of seeing the most fundamental unit of information.

  6. Entropy (information theory) - Wikipedia

    en.wikipedia.org/wiki/Entropy_(information_theory)

    Shannon's definition of entropy, when applied to an information source, can determine the minimum channel capacity required to reliably transmit the source as encoded binary digits. Shannon's entropy measures the information contained in a message as opposed to the portion of the message that is determined (or predictable).

  7. Binary symmetric channel - Wikipedia

    en.wikipedia.org/wiki/Binary_symmetric_channel

    Shannon's theorem gives us the best rate which could be achieved over a , but it does not give us an idea of any explicit codes which achieve that rate. In fact such codes are typically constructed to correct only a small fraction of errors with a high probability, but achieve a very good rate.

  8. A Mathematical Theory of Communication - Wikipedia

    en.wikipedia.org/wiki/A_Mathematical_Theory_of...

    Shannon's diagram of a general communications system, showing the process by which a message sent becomes the message received (possibly corrupted by noise) This work is known for introducing the concepts of channel capacity as well as the noisy channel coding theorem. Shannon's article laid out the basic elements of communication:

  9. Error correction code - Wikipedia

    en.wikipedia.org/wiki/Error_correction_code

    In general, a stronger code induces more redundancy that needs to be transmitted using the available bandwidth, which reduces the effective bit-rate while improving the received effective signal-to-noise ratio. The noisy-channel coding theorem of Claude Shannon can be used to compute the maximum achievable communication bandwidth for a given ...

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