What are the implications of the Markov property? What is a Markov chain?

the entropy rate of a stochastic process (message or sequence is seen as a succession of events). (The "rate of self-information" can also be defined for a ... Mar 15, 2023 ... Abstract. Some mathematical models of informational signals and methods of the diagnostic system construction is considered. Different type of ... Aug 8, 2024 ... Stochastic Processes and their Applications 55, 159 - 167 (1995). A stochastic process arising in sequential experimentation. Statistics ... Jul 25, 2023 ... The aggregated stochastic processes can be used to decribe evolution processes with group information observed, for example, the underlying ... ufacturing systems, information economics, stochastic processes and performance model- ing for capacity planning and pricing. Seidmann has consulted with ... ... stochastic processes or theoretical models. With the development of transfer ... In the bivariate case, information flow from process J to process I is ... If the stochastic process representing the belief over f is sufficiently regular, then Equation (1) can be approximated arbitrarily well with finitely many ... ... informational divergence between two Markov processes at ... Markov chains defined by a memoryless stochastic matrix correspond in fact to an iid process. General Information (Catalog listing). 01:640:478 Markov chains for discrete-time models, Poisson processes, Markov chains for continuous-time models, ... Let ξ , η be two random functions (= stationary (generalized) Gaussian random processes). The Gelfand–Pinsker–Yaglom functional (Formula (2.58) from [10]) for ...