Abstract. In this paper, we propose a new framework for the parametric verification of time Petri nets with stopwatches controlled by inhibitor arcs. We first introduce an extensio...
Louis-Marie Traonouez, Didier Lime, Olivier H. Rou...
This paper focuses on studying efficient solutions for modeling and deriving compositional tests for component-based real-time systems. In this work, we propose a coherent framewo...
Abstract. Existing algorithms for regular inference (aka automata learning) allows to infer a finite state machine by observing the output that the machine produces in response to ...
High-level stochastic description methods such as stochastic Petri nets, stochastic UML statecharts etc., together with specifications of performance variables (PVs), enable a co...
We suggest a recurrent neural network (RNN) model with a recurrent part corresponding to iterative function systems (IFS) introduced by Barnsley 1] as a fractal image compression ...