Information theory Also known as: Information theory · communication theory
Community · Information theory 1 Introduced the concept of the bit as the fundamental unit of information. 2 Established the Shannon entropy as a measure of uncertainty or information content. 3 Defined the channel capacity limit for reliable data transmission. 4 Provides the mathematical foundation for modern digital communication and data compression. 5 Influenced fields ranging from linguistics to computer science. Information theory is a scientific field concerned with the quantification, storage, and communication of information.
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Fundamental unit of information
The bit is the basic unit of information defined by information theory, representing the choice between two equally likely possibilities.
Foundational publication establishing the field
This 1948 paper by Claude Shannon is widely considered the seminal work that formally defined information theory and introduced its core concepts.
Entropy is a fundamental component of information theory.
Shannon entropy serves as the primary metric for quantifying information within the framework of information theory.
Shannon founded information theory.
Claude Shannon's 1948 paper 'A Mathematical Theory of Communication' is widely credited as the founding document of information theory.
Measure of statistical dependence
This quantity measures the amount of information obtained about one random variable through observing another, serving as a key metric in information theory.
Core theoretical limit of communication
This theorem defines the maximum rate at which information can be reliably transmitted over a noisy communication channel, a central pillar of information theory.
Institutional birthplace of the theory
The research environment at Bell Labs provided the practical telecommunications problems and intellectual resources that enabled Shannon to develop information theory.
Precursor to information theory
Hartley developed the 'Hartley measure' in 1928, which provided an early logarithmic quantification of information that directly influenced Shannon's work.
Technological implementation of information theory
These techniques utilize the principles of information theory to ensure reliable data transmission over unreliable or noisy communication channels.
Practical application of information theory
Information theory provides the mathematical bounds for data compression, explaining how much redundancy can be removed from a signal without losing information.
Interdisciplinary field sharing common roots
Information theory and cybernetics emerged concurrently in the mid-20th century, both focusing on the study of control and communication in systems.
Information theory is the formal mathematical study concerned with the quantification, storage, and communication of information. It provides the foundational framework for understanding how data can be measured and transmitted reliably across various media.
A picture showing scratches on the readable surface of a CD-R. Music and data CDs are coded using error correcting codes and thus can still be read even if they have minor scratches using error detection and correction. Wikimedia Commons: File:CDSCRATCHES.jpg The entropy of a Bernoulli trial as a function of success probability, often called the binary entropy function, b (''p'')"}},"i":0}}]}"> H b ( p ). The entropy is maximized at 1 bit per trial when the two possible outcomes are equally probable, as in an unbiased coin toss. Wikimedia Commons: File:Binary_entropy_plot.svg The field was established in the 1940s by the mathematician Claude Shannon , who formalized its core principles. Earlier essential contributions were made during the 1920s by researchers Harry Nyquist and Ralph Hartley , whose work laid the groundwork for the later developments in the discipline.
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