Abstract— Frequency dependent interconnect analysis is challenging since lumped equivalent circuit models extracted at different frequencies exhibit distinct time and frequency d...
Uncertainty is omnipresent when we perceive or interact with our environment, and the Bayesian framework provides computational methods for dealing with it. Mathematical models fo...
Bernhard Nessler, Michael Pfeiffer, Wolfgang Maass
This paper examines knowledge sharing processes in digital government projects (DGPs). Although knowledge sharing processes are a central feature of the functioning of government,...
We consider the problem of finding a sparse set of edges containing the minimum spanning tree (MST) of a random subgraph of G with high probability. The two random models that we ...
This work exploits several machine-learning techniques to address the problem of image-quality prediction of synthetic aperture sonar (SAS) imagery. The objective is to predict th...