Search results
Results from the WOW.Com Content Network
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.
2003 – David J. C. MacKay shows the connection between information theory, inference and machine learning in his book. 2006 – Jarosław Duda introduces first Asymmetric numeral systems entropy coding: since 2014 popular replacement of Huffman and arithmetic coding in compressors like Facebook Zstandard, Apple LZFSE, CRAM or JPEG XL
Information theory is a branch of applied mathematics, electrical engineering, and computer science involving the quantification of information. Information theory was developed by Claude E. Shannon to find fundamental limits on signal processing operations such as compressing data and on reliably storing and communicating data.
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 ...
Charles S. Peirce's theory of information was embedded in his wider theory of symbolic communication he called the semiotic, now a major part of semiotics. For Peirce, information integrates the aspects of signs and expressions separately covered by the concepts of denotation and extension , on the one hand, and by connotation and comprehension ...
entropy (information theory) Fisher information; Hick's law; Huffman coding; information bottleneck method; information theoretic security; information theory; joint entropy; Kullback–Leibler divergence; lossless compression; negentropy; noisy-channel coding theorem (Shannon's theorem) principle of maximum entropy; quantum information science ...
The information bottleneck method is a technique in information theory introduced by Naftali Tishby, Fernando C. Pereira, and William Bialek. [1] It is designed for finding the best tradeoff between accuracy and complexity (compression) when summarizing (e.g. clustering) a random variable X, given a joint probability distribution p(X,Y) between X and an observed relevant variable Y - and self ...
Information flow (information theory) Information fluctuation complexity; Information–action ratio; Information projection; Information source (mathematics) Information theory and measure theory; Integrated information theory; Interaction information; Interactions of actors theory; Interference channel