In electrical engineering, computer science and information theory, channel capacity is the tightest upper bound on the amount of information that can be reliably transmitted over a communications channel. By the noisy-channel coding theorem, the channel capacity of a given channel is the limiting information rate (in units of information per unit time) that can be achieved with arbitrarily small error probability.
Information theory, developed by Claude E. Shannon during World War II, defines the notion of channel capacity and provides a mathematical model by which one can compute it. 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 maximization is with respect to the input distribution.
Read more about Channel Capacity: Formal Definition, Noisy-channel Coding Theorem, Example Application, Channel Capacity in Wireless Communications
Famous quotes containing the words channel and/or capacity:
“Children belong in families, which, ideally, serve as a sanctuary and a cushion from the world at large. Parents belong to society and are a part of that greater world. Sometimes parents are a channel to the larger society, sometimes they are a shield from it. Ideally they act as filters, guiding their children and teaching them to avoid the tempting trash.”
—Louise Hart (20th century)
“If the only new thing we have to offer is an improved version of the past, then today can only be inferior to yesterday. Hypnotised by images of the past, we risk losing all capacity for creative change.”
—Robert Hewison (b. 1943)