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  2. Shannon–Hartley theorem - Wikipedia

    en.wikipedia.org/wiki/ShannonHartley_theorem

    The concept of an error-free capacity awaited Claude Shannon, who built on Hartley's observations about a logarithmic measure of information and Nyquist's observations about the effect of bandwidth limitations. Hartley's rate result can be viewed as the capacity of an errorless M-ary channel of symbols per second. Some authors refer to it as a ...

  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 ShannonHartley 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. Channel capacity - Wikipedia

    en.wikipedia.org/wiki/Channel_capacity

    This result is known as the ShannonHartley theorem. [11] When the SNR is large (SNR ≫ 0 dB), the capacity ⁡ ¯ is logarithmic in power and approximately linear in bandwidth. This is called the bandwidth-limited regime.

  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 ShannonHartley 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. Category:Mathematical theorems in theoretical computer ...

    en.wikipedia.org/wiki/Category:Mathematical...

    Download as PDF; Printable version; In other projects Wikidata item; Appearance. move to sidebar hide. Help ... ShannonHartley theorem; Shannon's source coding theorem

  7. 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:

  8. Signal-to-noise ratio - Wikipedia

    en.wikipedia.org/wiki/Signal-to-noise_ratio

    This relationship is described by the ShannonHartley theorem, which is a fundamental law of information theory. SNR can be calculated using different formulas depending on how the signal and noise are measured and defined.

  9. Carrier-to-noise ratio - Wikipedia

    en.wikipedia.org/wiki/Carrier-to-noise_ratio

    In the famous ShannonHartley theorem, the C/N ratio is equivalent to the S/N ratio. The C/N ratio resembles the carrier-to-interference ratio (C/I, CIR), and the carrier-to-noise-and-interference ratio, C/(N+I) or CNIR. C/N estimators are needed to optimize the receiver performance. [1]