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  2. Markov's principle - Wikipedia

    en.wikipedia.org/wiki/Markov's_principle

    Markov's principle (also known as the Leningrad principle [1]), named after Andrey Markov Jr, is a conditional existence statement for which there are many equivalent formulations, as discussed below. The principle is logically valid classically, but not in intuitionistic constructive mathematics. However, many particular instances of it are ...

  3. Markov algorithm - Wikipedia

    en.wikipedia.org/wiki/Markov_algorithm

    In theoretical computer science, a Markov algorithm is a string rewriting system that uses grammar-like rules to operate on strings of symbols. Markov algorithms have been shown to be Turing-complete , which means that they are suitable as a general model of computation and can represent any mathematical expression from its simple notation.

  4. Template:Markov constant chart - Wikipedia

    en.wikipedia.org/wiki/Template:Markov_constant_chart

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  5. Markov theorem - Wikipedia

    en.wikipedia.org/wiki/Markov_theorem

    More precisely Markov's theorem can be stated as follows: [2] [3] given two braids represented by elements , ′ in the braid groups ,, their closures are equivalent links if and only if ′ can be obtained from applying to a sequence of the following operations:

  6. Markov operator - Wikipedia

    en.wikipedia.org/wiki/Markov_operator

    In probability theory and ergodic theory, a Markov operator is an operator on a certain function space that conserves the mass (the so-called Markov property). If the underlying measurable space is topologically sufficiently rich enough, then the Markov operator admits a kernel representation. Markov operators can be linear or non-linear.

  7. Causal Markov condition - Wikipedia

    en.wikipedia.org/wiki/Causal_Markov_condition

    The related Causal Markov (CM) condition states that, conditional on the set of all its direct causes, a node is independent of all variables which are not effects or direct causes of that node. [3] In the event that the structure of a Bayesian network accurately depicts causality , the two conditions are equivalent.

  8. Markov property - Wikipedia

    en.wikipedia.org/wiki/Markov_property

    The term Markov assumption is used to describe a model where the Markov property is assumed to hold, such as a hidden Markov model. A Markov random field extends this property to two or more dimensions or to random variables defined for an interconnected network of items. [1] An example of a model for such a field is the Ising model.

  9. Markov chain - Wikipedia

    en.wikipedia.org/wiki/Markov_chain

    Markov processes can also be used to generate superficially real-looking text given a sample document. Markov processes are used in a variety of recreational "parody generator" software (see dissociated press, Jeff Harrison, [103] Mark V. Shaney, [104] [105] and Academias Neutronium). Several open-source text generation libraries using Markov ...