Markov processes form a fundamental class of stochastic models in which the evolution of a system is delineated by the memoryless property. In such processes, the future state depends solely on the ...

https://doi.org/10.2307/1426942 • https://www.jstor.org/stable/1426942 Copy URL A stationary process yt,t∈ R1 is considered which is Markov between points of ...

The Annals of Statistics, Vol. 4, No. 6 (Nov., 1976), pp. 1219-1235 (17 pages) The paper deals with continuous time Markov decision processes on a fairly general state space. The rewards are ...

The study of Dirichlet forms and Markov processes in fractal geometry offers a robust framework for analysing irregular spaces that do not conform to classical Euclidean structures. Dirichlet forms ...

Content: In this lecture we analyse the class of Markov processes in continuous time. We start with a focus on processes processes in discrete state spaces. For this we introduce point processes as a ...

Systematic study of Markov chains and some of the simpler Markov processes including renewal theory, limit theorems for Markov chains, branching processes, queuing theory, birth and death processes, ...

The amino acid sequence of the transmembrane protein and its corresponding positions on the cell membrane are transformed into a hidden Markov process. After evaluating the parameters, the Viterbi ...