Semi-Markov processes extend traditional Markov models by explicitly accounting for the time spent in each state before transitioning. This added temporal dimension is particularly valuable in credit ...

Discover how Markov chains predict real systems, from Ulam and von Neumann’s Monte Carlo to PageRank, so you can grasp ...

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 ...

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 ...

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 ...

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 ...

We consider a singularly perturbed (finite state) Markov chain and provide a complete characterization of the fundamental matrix. In particular, we obtain a formula for the regular part simpler than a ...

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 ...