markov process वाक्य
उदाहरण वाक्य
मोबाइल
- The Brownian motion process and the Poisson process ( in one dimension ) are both examples of Markov processes.
- Because " r " is governed by a Markov process, dynamic programming simplifies the problem significantly.
- In the same thesis he considered the problem of applying Markov processes to the solution of partial differential equations.
- Andrei Kolmogorov developed in a 1931 paper a large part of the early theory of continuous-time Markov processes.
- This theory was concerned with the mathematical foundations of the theory of continuous time stochastic processes, especially Markov processes.
- In brief, the evolution of a genetic sequence is modelled by a time-reversible continuous time Markov process.
- The adjective "'Markovian "'is used to describe something that is related to a Markov process.
- There are many examples of Markov processes, Gaussian processes, and other processes that can be enhanced as rough paths.
- Certain Dirichlet forms can be used to study partial differential equations and link them to the probabilistic setting of Markov processes.
- The distribution can be represented by a random variable describing the time until absorption of a Markov process with one absorbing state.
- On Markov processes it has been carried out mostly in the United States by Doob, T E Harris and the reviewer.
- The Wiener process is a member of some important families of stochastic processes, including Markov processes, L�vy processes and Gaussian processes.
- The same condition is valid for the reversible Markov processes ( it is equivalent to the " no net flow " condition ).
- He found that there are two kinds of continuous time Markov processes, depending on the assumed behavior over small intervals of time:
- In 1982 he gave a plenary address ( " Optimal control of Markov Processes " ) at the ICM in Warsaw.
- These nonlinear Markov processes and their mean field particle interpretation can be extended to time non homogeneous models on general measurable state spaces.
- Random walks on the integers and the Gambler's ruin problem are examples of Markov processes and were studied hundreds of years earlier.
- A strictly stationary Markov process is " ? "-mixing if and only if it is an aperiodic recurrent Harris chain.
- IPS are usually defined via their Markov generator giving rise to a unique Markov process using Markov semigroups and the Hille-Yosida theorem.
- The basic idea of the MCAM is to approximate the original controlled process by a chosen controlled markov process on a finite state space.
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