Information Theory

Information theory is the scientific study of the quantification, storage, and communication of digital information. The field was fundamentally established by the works of Harry Nyquist and Ralph Hartley, in the 1920s, and Claude Shannon in the 1940s.: vii  The field is at the intersection of probability theory, statistics, computer science, statistical mechanics, information engineering, and electrical engineering.A key measure in information theory is entropy. Entropy quantifies the amount of uncertainty involved in the value of a random variable or the outcome of a random process. For example, identifying the outcome of a fair coin flip (with two equally likely outcomes) provides less information (lower entropy) than specifying the outcome from a roll of a die (with six equally likely outcomes). Some other important measures in information theory are mutual information, channel capacity, error exponents, and relative entropy. Important sub-fields of information theory include source coding, algorithmic complexity theory, algorithmic information theory and information-theoretic security.Covers theoretical and experimental aspects of information theory and coding. Includes material in ACM Subject Class E.4 and intersects with H.1.1.
相关学科: Networking and Internet ArchitectureQuantizationConvolutionFrequency Division MultiplexingDiscrete MathematicsCryptography and SecurityCompressive SensingMLTime SeriesGPS









Jean-François Cardoso

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Michael I. Jordan

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Yang Yang

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Terrence J. Sejnowski

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Stephen Boyd

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John R. Yates

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Claude E. Shannon

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David Cox

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