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11 relations: Communication theory, Entropy rate, Hidden Markov model, Information source (mathematics), Markov chain, Mathematics, Natural language processing, Random variable, Stationary distribution, Transmitter, Viterbi algorithm.
Communication theory
Communication theory is a field of information theory and mathematics that studies the technical process of information and the process of human communication.
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Entropy rate
In the mathematical theory of probability, the entropy rate or source information rate of a stochastic process is, informally, the time density of the average information in a stochastic process.
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Hidden Markov model
Hidden Markov Model (HMM) is a statistical Markov model in which the system being modeled is assumed to be a Markov process with unobserved (i.e. hidden) states.
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Information source (mathematics)
In mathematics, an information source is a sequence of random variables ranging over a finite alphabet Γ, having a stationary distribution.
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Markov chain
A Markov chain is "a stochastic model describing a sequence of possible events in which the probability of each event depends only on the state attained in the previous event".
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Mathematics
Mathematics (from Greek μάθημα máthēma, "knowledge, study, learning") is the study of such topics as quantity, structure, space, and change.
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Natural language processing
Natural language processing (NLP) is an area of computer science and artificial intelligence concerned with the interactions between computers and human (natural) languages, in particular how to program computers to process and analyze large amounts of natural language data.
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Random variable
In probability and statistics, a random variable, random quantity, aleatory variable, or stochastic variable is a variable whose possible values are outcomes of a random phenomenon.
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Stationary distribution
Stationary distribution may refer to.
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Transmitter
In electronics and telecommunications, a transmitter or radio transmitter is an electronic device which produces radio waves with an antenna.
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Viterbi algorithm
The Viterbi algorithm is a dynamic programming algorithm for finding the most likely sequence of hidden states—called the Viterbi path—that results in a sequence of observed events, especially in the context of Markov information sources and hidden Markov models.
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