The Theory And Methods Of Revolution - amazonia.fiocruz.br

The Theory And Methods Of Revolution Video

Information theory studies the quantificationstorageand communication of information.

It was originally proposed by Claude Shannon in to find fundamental limits on signal processing and communication operations such as data compressionin a landmark paper titled " A Mathematical Theory of Communication ". The field is at the intersection of probability theorystatisticscomputer science, statistical mechanicsinformation engineeringand electrical engineering. A key measure in information theory is entropy. Entropy quantifies the amount of uncertainty involved in the value of a random variable or the outcome of a random process. For example, identifying the outcome of a fair coin flip with two equally likely outcomes provides less information lower entropy than specifying the outcome from a roll of a dice with six The Theory And Methods Of Revolution likely outcomes.

Some other important measures in information theory are mutual informationchannel capacity, error exponentsand relative entropy. Important sub-fields of information theory include source codingalgorithmic complexity theoryalgorithmic information theoryand information-theoretic security.

Applications of fundamental topics of information theory include lossless data compression e. ZIP fileslossy data compression e. Its impact has been crucial to the success of the Voyager missions to deep space, the invention of the compact discthe feasibility of mobile phones and the development of the Internet.

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Read more theory has also found applications in other areas, including statistical inference[1] cryptographyneurobiology[2] perception[3] linguistics, the evolution [4] and function [5] of molecular codes bioinformaticsthermal physics[6] quantum computingblack holes, linguistics, information retrievalintelligence gatheringplagiarism detection[7] pattern recognitionanomaly detection [8] and even art creation. Information theory studies the transmission, processing, extraction, and utilization of information. Abstractly, information can be thought of as the resolution of uncertainty. In the case of communication of information over a noisy channel, this abstract concept was made concrete in by Claude Shannon in his paper "A Mathematical Theory of Communication", in which "information" is thought of as a set of possible messages, where the goal is to send these messages over a noisy channel, and then to have the receiver reconstruct the message with low probability of error, in spite of the channel noise.

Shannon's main result, the noisy-channel coding theorem showed that, in The Theory And Methods Of Revolution limit of many channel uses, the rate of information that is asymptotically achievable is equal to the channel capacity, a quantity dependent merely on the statistics of the channel over which the messages are sent.]