enow.com Web Search

Search results

1. Results from the WOW.Com Content Network

2. Shannon–Hartley theorem - Wikipedia

   en.wikipedia.org/wiki/Shannon–Hartley_theorem

   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 specified bandwidth in the presence of the noise interference, assuming that the signal power is bounded, and that the Gaussian noise process is characterized by a ...

3. Entropy (information theory) - Wikipedia

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

   The concept of information entropy was introduced by Claude Shannon in his 1948 paper "A Mathematical Theory of Communication", [2] [3] and is also referred to as Shannon entropy. Shannon's theory defines a data communication system composed of three elements: a source of data, a communication channel, and a receiver. The "fundamental problem ...

4. Limiting density of discrete points - Wikipedia

   en.wikipedia.org/wiki/Limiting_density_of...

   Shannon originally wrote down the following formula for the entropy of a continuous distribution, known as differential entropy: = ⁡ ().Unlike Shannon's formula for the discrete entropy, however, this is not the result of any derivation (Shannon simply replaced the summation symbol in the discrete version with an integral), and it lacks many of the properties that make the discrete entropy a ...

5. Information content - Wikipedia

   en.wikipedia.org/wiki/Information_content

   As a quick illustration, the information content associated with an outcome of 4 heads (or any specific outcome) in 4 consecutive tosses of a coin would be 4 shannons (probability 1/16), and the information content associated with getting a result other than the one specified would be ~0.09 shannons (probability 15/16).

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. Noisy-channel coding theorem - Wikipedia

   en.wikipedia.org/wiki/Noisy-channel_coding_theorem

   In information theory, the noisy-channel coding theorem (sometimes Shannon's theorem or Shannon's limit), establishes that for any given degree of noise contamination of a communication channel, it is possible (in theory) to communicate discrete data (digital information) nearly error-free up to a computable maximum rate through the channel.