High-order Markov chain models extend the conventional framework by incorporating dependencies that span several previous states rather than solely the immediate past. This extension allows for a ...

This is a preview. Log in through your library . Abstract We have two aims in this paper. First, we generalize the well-known theory of matrix-geometric methods of Neuts to more complicated Markov ...

Brief review of conditional probability and expectation followed by a study of Markov chains, both discrete and continuous time. Queuing theory, terminology, and single queue systems are studied with ...

We focus our attention herein on a Markov chain $x_0, x_1, \cdots$ with a countable number of states indexed by a subset I of the integers and with stationary ...

Forbes contributors publish independent expert analyses and insights. Dr. Lance B. Eliot is a world-renowned AI scientist and consultant. In today’s column, I closely examine an innovative way of ...

If we can ‘talk’ to AI programs today, it’s in part because of a Russian from the 1800s. Markov’s approach to data in flux changed how we navigate our world. There’s an odd little trick to how AI ...