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He further wrote a paper in 1956 regarding coding for a noisy channel, which also became a classic paper in the field of information theory. [61] Claude Shannon's influence has been immense in the field, for example, in a 1973 collection of the key papers in the field of information theory, he was author or coauthor of 12 of the 49 papers cited ...
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 ...
The sampling theory of Shannon can be generalized for the case of nonuniform sampling, that is, samples not taken equally spaced in time. The Shannon sampling theory for non-uniform sampling states that a band-limited signal can be perfectly reconstructed from its samples if the average sampling rate satisfies the Nyquist condition. [5]
It also developed the concepts of information entropy, redundancy and the source coding theorem, and introduced the term bit (which Shannon credited to John Tukey) as a unit of information. It was also in this paper that the Shannon–Fano coding technique was proposed – a technique developed in conjunction with Robert Fano.
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.
"Communication Theory of Secrecy Systems" is a paper published in 1949 by Claude Shannon discussing cryptography from the viewpoint of information theory. [1] It is one of the foundational treatments (arguably the foundational treatment) of modern cryptography. [ 2 ]
The publication of Shannon's 1948 paper, "A Mathematical Theory of Communication", in the Bell System Technical Journal was the founding of information theory as we know it today. Many developments and applications of the theory have taken place since then, which have made many modern devices for data communication and storage such as CD-ROMs ...
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 ...