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  2. Shannon–Hartley theorem - Wikipedia

    en.wikipedia.org/wiki/ShannonHartley_theorem

    In the channel considered by the Shannon–Hartley theorem, noise and signal are combined by addition. That is, the receiver measures a signal that is equal to the sum of the signal encoding the desired information and a continuous random variable that represents the noise. This addition creates uncertainty as to the original signal's value.

  3. Channel capacity - Wikipedia

    en.wikipedia.org/wiki/Channel_capacity

    The computational complexity of finding the Shannon capacity of such a channel remains open, ... (SNR). This result is known as the Shannon–Hartley theorem. [11]

  4. 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 ...

  5. Template:Information theory - Wikipedia

    en.wikipedia.org/wiki/Template:Information_theory

    Channel capacity; Noisy-channel coding theorem; Shannon–Hartley theorem; Template documentation This page was last edited on 6 January 2023, at 10:06 (UTC). ...

  6. 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.

  7. Shannon capacity of a graph - Wikipedia

    en.wikipedia.org/wiki/Shannon_capacity_of_a_graph

    In graph theory, the Shannon capacity of a graph is a graph invariant defined from the number of independent sets of strong graph products. It is named after American mathematician Claude Shannon . It measures the Shannon capacity of a communications channel defined from the graph, and is upper bounded by the Lovász number , which can be ...

  8. Computer engineering compendium - Wikipedia

    en.wikipedia.org/wiki/Computer_engineering...

    Channel capacity Shannon–Hartley theorem Nyquist–Shannon sampling theorem Shannon's source coding theorem Zero-order hold Data compression Modulation order

  9. Shaping codes - Wikipedia

    en.wikipedia.org/wiki/Shaping_codes

    C is the channel capacity in bits per second; B is the bandwidth of the channel in hertz; S is the total signal power over the bandwidth and N is the total noise power over the bandwidth. S/N is the signal-to-noise ratio of the communication signal to the Gaussian noise interference expressed as a straight power ratio (not as decibels).