We investigate the discrete (finite) case of the Popper-Renyi theory of conditional probability, introducing discrete conditional probabilistic models for (multi-agent) knowledge...
Abstract—Mapping stationary objects is essential for autonomous vehicles and many autonomous functions in vehicles. In this contribution the probability hypothesis density (PHD) ...
Christian Lundquist, Lars Hammarstrand, Fredrik Gu...
A generalized or tunable-kernel model is proposed for probability density function estimation based on an orthogonal forward regression procedure. Each stage of the density estimat...
Abstract: A probabilistic event-driven fault localization technique is presented, which uses a symptom-fault map as a fault propagation model. The technique isolates the most proba...
This paper presents a probabilistic event-driven fault localization technique, which uses a probabilistic symptomfault map as a fault propagation model. The technique isolates the...