Q-learning, a most widely used reinforcement learning method, normally needs well-defined quantized state and action spaces to converge. This makes it difficult to be applied to re...
This paper presents a comprehensive formulation of a linearized state space process model for a generic two-reactant-two-product reactive distillation system. The development of t...
`Approximate message passing' algorithms proved to be extremely effective in reconstructing sparse signals from a small number of incoherent linear measurements. Extensive num...
This paper studies abstraction and refinement techniques in the setting of multi-valued model checking for the μ-calculus. Two dimensions of abstrace identified and studied: Abs...
Alarico Campetelli, Alexander Gruler, Martin Leuck...
This paper describes a no-reference temporal quality metric to model the impact of frame freezing impairments on perceived video quality. The proposed metric shows a high correlat...