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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.
If the requirement is to transmit at 50 kbit/s, and a bandwidth of 10 kHz is used, then the minimum S/N required is given by 50000 = 10000 log 2 (1+S/N) so C/B = 5 then S/N = 2 5 − 1 = 31, corresponding to an SNR of 14.91 dB (10 x log 10 (31)). What is the channel capacity for a signal having a 1 MHz bandwidth, received with a SNR of −30 dB ?
The Shannon capacity of a graph G is bounded from below by α(G), and from above by ϑ(G). [5] In some cases, ϑ(G) and the Shannon capacity coincide; for instance, for the graph of a pentagon, both are equal to √ 5. However, there exist other graphs for which the Shannon capacity and the Lovász number differ. [6]
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.
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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:
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The 2024 Heisman Trophy ceremony is Saturday. Here is a list of past winners for the coveted college football award.