Harry Nyquist's 1924 paper, Certain Factors Affecting Telegraph Speed, contains a theoretical section quantifying "intelligence" and the "line speed" at which it can be transmitted by a communication system, giving the relation W = K log m (recalling Boltzmann's constant), where W is the speed of transmission of intelligence, m is the number of different voltage levels to choose from at each time step, and K is a constant. The choice of logarithmic base in the following formulae determines the unit of information entropy that is used. = Some other important measures in information theory are mutual information, channel capacity, error exponents, and relative entropy. Information theoretic security refers to methods such as the one-time pad that are not vulnerable to such brute force attacks. Another interpretation of the KL divergence is the "unnecessary surprise" introduced by a prior from the truth: suppose a number X is about to be drawn randomly from a discrete set with probability distribution p(x). Network information theory refers to these multi-agent communication models. Information and communication technology (ICT) systems are widely used in organizations. Other bases are also possible, but less commonly used. A common unit of information is the bit, based on the binary logarithm. (Here, I(x) is the self-information, which is the entropy contribution of an individual message, and X is the expected value.) The new technologies are introducing many changes to mass communication, and communication theories must be developed or revised to keep up with the changes. Coding theory is concerned with finding explicit methods, called codes, for increasing the efficiency and reducing the error rate of data communication over noisy channels to near the channel capacity. These can be obtained via extractors, if done carefully. For example, if (X, Y) represents the position of a chess piece—X the row and Y the column, then the joint entropy of the row of the piece and the column of the piece will be the entropy of the position of the piece. Control of communication technology and information becomes a significant way for corporations and governments to economic, social, and cultural influence over citizens and groups, influence not obtained through conventional educational or political means. Between these two extremes, information can be quantified as follows. In the case of communication of information over a noisy channel, this abstract concept was made concrete in 1948 by Claude Shannon in his paper "A Mathematical Theory of Communication", in which "information" is thought of as a set of possible messages, where the goal is to send these messages over a noisy channel, and then to have the receiver reconstruct the message with low probability of error, in spite of the channel noise. MP3s and JPEGs), and channel coding (e.g. Ralph Hartley's 1928 paper, Transmission of Information, uses the word information as a measurable quantity, reflecting the receiver's ability to distinguish one sequence of symbols from any other, thus quantifying information as H = log Sn = n log S, where S was the number of possible symbols, and n the number of symbols in a transmission. All About Theories for Communication. Based on the probability mass function of each source symbol to be communicated, the Shannon entropy H, in units of bits (per symbol), is given by. {\displaystyle \lim _{p\rightarrow 0+}p\log p=0} log for DSL). sharone. Register to receive personalised research and resources by email, Critical Theory of Communication Technology: Introduction to the Special Section, Applied Communication and Technology Laboratory, School of Communication , Simon Fraser University , Vancouver, British Columbia, Canada, /doi/full/10.1080/01972240802701536?needAccess=true. April 25, 2016 at 3:20 pm highly informative..thank you.

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