Regarding nite state machines as Markov chains facilitates the application of probabilistic methods to very large logic synthesis and formal verication problems. Recently, we ha...
Gary D. Hachtel, Enrico Macii, Abelardo Pardo, Fab...
In this paper, we develop a model for representing term dependence based on Markov Random Fields and present an approach based on Markov Chain Monte Carlo technique for generating ...
Numerous techniques exist which can be used for the task of behavioural analysis and recognition. Common amongst these are Bayesian networks and Hidden Markov Models. Although the...
David Paul Young, James M. Ferryman, Nicholas L. C...
We consider a networked control system, where each subsystem evolves as a Markov decision process (MDP). Each subsystem is coupled to its neighbors via communication links over wh...
–The performability of disk arrays systems has been studied before. However, in the case of imprecise data, a fuzzy model can be the base for the performability analysis. This pa...