In general a Liapunov function W is a positive function which grows at infinity and satisfies an inequality involving the generator of the Markov process L: roughly speaking we have the implications (伪 and 尾 are positive constants)doi:10.1007/3-540-33966-3_1Luc Rey Bellet...
we recommend the articles of Kliemann [4], Kunita [6], Norris [8], and Stroock and Varadhan [12] and the book of H¨ ormander [1]. 2 Stochastic Processes A stochastic process is a parametrized collection of random variables {x t (ω)} t∈T (1) Ergodic Properties of Markov Process...
In general a Liapunov function W is a positive function which grows at infinity and satisfies an inequality involving the generator of the Markov process L: roughly speaking we have the implications (α and β are positive constants) 展开 ...
Dynamics of infinite particle systems and Gibbs point random fields The Euler equations for the one-dimensional zero range process Probability And Theoretical Physics (Session 27 - Chairman: K.R. Parthasarathy) Invited Papers Recent developments in quantum probability Markov operators on quantum ...
MarkovProcessProperties[mproc] gives a summary of properties for the finite state Markov process mproc. MarkovProcessProperties[mproc, " property"] gives the specified " property" for the process mproc.
Probabilistic Properties of a Nonlinear ARMA Process with Markov Switching We consider a nonlinear autoregressive moving average (ARMA) process with Markov switching and find sufficient conditions for strict stationarity, geometric ergodicity, and the existence of moments of the process with respect to the...
Piecewise deterministic Markov processConvergence to equilibriumDifferential inclusionHormander bracket conditionWe study a class of Piecewise Deterministic Markov Processes with state space Rd x E where E is a finite set. The continuous component evolves according to a smooth vector field that is switched...
Cooperative Decision-Making to Minimize Biased Perceived Value Effect on Business Process Decisions Using Partially Observable Markov Decision Processes Deciding what options to take while a business process operate is recurrently challenged by the problem of incomplete information that is available to the ...
The paper deals with the problem of temporary reversibility for Markov processes and its consequences in the analysis of dynamic Markov processes. The appropriate definitions of reversibility introduced have made it possible to consider a general class of non-stationary Markov processes. The necessary an...
Goulionis JE: Structural properties for a two-state partially observable Markov decision process with an average cost criterion. Journal of Statistics & Management Systems. 2007, 10 (5): 715-733.Goulionis JE: Structural properties for a two-state partially observable Markov decision process with ...