A bivariate Markov process comprises a pair of random processes which are jointly Markov. One of the two processes in that pair is observable while the other plays the role of an underlying process. We are interested in three classes of bivariate Markov processes. In the first and major class of interest, the underlying and observable processes are continuous-time with finite alphabet; in the s...

A technique is developed for comparing a non-Markov process to a Markov process on a general state space with many possible stochastic orderings. Two such comparisons with a common Markov process yield a comparison between two non-Markov processes. The technique, which is based on stochastic monotonidty of the Markov process, yields stochastic comparisons of the limiting distributions and the m...

Process adjustment, also known as process targeting, is one of the classical problems in the field of quality control and production economics. In the process adjustment problem, it is assumed that process parameters are variables and the aim is to determine these parameters such that certain economic criteria are optimally satisfied. The aim of this paper is to determine the optimal process ad...

A new Markov-based method for real time prediction of network transmission time delays is introduced. The method considers a Multi-Layer Perceptron (MLP) neural model for the transmission network, where the number of neurons in the input layer is minimized so that the required calculations are reduced and the method can be implemented in the real-time. For this purpose, the Markov process order...