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In mathematics — specifically, in stochastic analysis — the infinitesimal generator of a Feller process (i.e. a continuous-time Markov process satisfying certain regularity conditions) is a Fourier multiplier operator [1] that encodes a great deal of information about the process. The generator is used in evolution equations such as the ...
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, [110] Mark V. Shaney, [111] [112] and Academias Neutronium). Several open-source text generation libraries using Markov ...
A Feller process is a Markov process with a Feller transition function. Generator. Feller processes ... The operator A is the generator of T t, ...
A continuous-time Markov chain (CTMC) is a continuous stochastic process in which, for each state, the process will change state according to an exponential random variable and then move to a different state as specified by the probabilities of a stochastic matrix. An equivalent formulation describes the process as changing state according to ...
In probability theory, a transition-rate matrix (also known as a Q-matrix, [1] intensity matrix, [2] or infinitesimal generator matrix [3]) is an array of numbers describing the instantaneous rate at which a continuous-time Markov chain transitions between states.
A Markov arrival process is defined by two matrices, D 0 and D 1 where elements of D 0 represent hidden transitions and elements of D 1 observable transitions. The block matrix Q below is a transition rate matrix for a continuous-time Markov chain.
In mathematics, the term infinitesimal generator may refer to: an element of the Lie algebra, associated to a Lie group; Infinitesimal generator (stochastic processes), of a stochastic process; infinitesimal generator matrix, of a continuous time Markov chain, a class of stochastic processes; Infinitesimal generator of a strongly continuous ...
In probability theory, a piecewise-deterministic Markov process (PDMP) is a process whose behaviour is governed by random jumps at points in time, but whose evolution is deterministically governed by an ordinary differential equation between those times.