In this paper we present a probabilistic framework for tracking objects based on local dynamic segmentation. We view the segn to be a Markov labeling process and abstract it as a ...
Emerging applications using miniature electronic devices (e.g., tracking mobile objects using sensors) generate very large amounts of highly dynamic data that poses very high overh...
Systems of ordinary differential equations (ODEs) are often used to model the dynamics of complex biological pathways. We construct a discrete state model as a probabilistic appro...
State spaces are commonly used representations of system behavior. A state space may be derived from a model of system behavior but can also be obtained through process mining. For...
H. M. W. (Eric) Verbeek, A. Johannes Pretorius, Wi...
High-level semi-Markov modelling paradigms such as semi-Markov stochastic Petri nets and process algebras are used to capture realistic performance models of computer and communic...
Marcel C. Guenther, Nicholas J. Dingle, Jeremy T. ...