Information theory

Topic | v1 | created by janarez |

Information theory is the scientific study of the quantification, storage, and communication of digital information. The field was fundamentally established by the works of Harry Nyquist and Ralph Hartley, in the 1920s, and Claude Shannon in the 1940s. The field is at the intersection of probability theory, statistics, computer science, statistical mechanics, information engineering, and 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 die (with six equally likely outcomes). Some other important measures in information theory are mutual information, channel capacity, error exponents, and relative entropy.


important for | used by Data compression

In signal processing, data compression, source coding, or bit-rate reduction is the process of encodi...

created by Claude Shannon

Claude Elwood Shannon (April 30, 1916 – February 24, 2001) was an American mathematician, electrical...

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treated in Elements of Information Theory

Preface to the Second Edition. Preface to the First Edition. Acknowledgments for the Second Edition....

has official A mathematical theory of communication

The recent development of various methods of modulation such as PCM and PPM which exchange bandwidth...