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The landmark event establishing the discipline of information theory and bringing it to immediate worldwide attention was the publication of Claude E. Shannon's classic paper "A Mathematical Theory of Communication" in the Bell System Technical Journal in July and October 1948.
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 ...
A documentary on Claude Shannon and on the impact of information theory, The Bit Player, was produced by Sergio Verdú and Mark Levinson. [115] A trans-Atlantic celebration of both George Boole's bicentenary and Claude Shannon's centenary that is being led by University College Cork and the Massachusetts Institute of Technology.
Capacity of the two-way channel: The capacity of the two-way channel (a channel in which information is sent in both directions simultaneously) is unknown. [ 5 ] [ 6 ] Capacity of Aloha : The ALOHAnet used a very simple access scheme for which the capacity is still unknown, though it is known in a few special cases.
In information theory, Shannon's source coding theorem (or noiseless coding theorem) establishes the statistical limits to possible data compression for data whose source is an independent identically-distributed random variable, and the operational meaning of the Shannon entropy. Named after Claude Shannon, the source coding theorem shows that ...
The defining expression for entropy in the theory of information established by Claude E. Shannon in 1948 is of the form: = , where is the probability of the message taken from the message space M, and b is the base of the logarithm used.
A Mind at Play: How Claude Shannon Invented the Information Age is a biography of Claude Shannon, an American mathematician, electrical engineer, and cryptographer known as "the father of information theory". [1] [2] The biography was written by Jimmy Soni and Rob Goodman, and published by Simon & Schuster in 2017.
The Shannon information is closely related to entropy, which is the expected value of the self-information of a random variable, quantifying how surprising the random variable is "on average". This is the average amount of self-information an observer would expect to gain about a random variable when measuring it.