Bayesian estimation in nonlinear stochastic dynamical systems has been addressed for a long time. Among other solutions, Particle Filtering (PF) algorithms propagate in time a Mon...
The class of stochastic nonlinear programming (SNLP) problems is important in optimization due to the presence of nonlinearity and uncertainty in many applications, including thos...
Network tomography is a process for inferring "internal" link-level delay and loss performance information based on end-to-end (edge) network measurements. These methods...
Mark Coates, Rui Castro, Robert Nowak, Manik Gadhi...
Abstract. Most of the approaches dedicated to fiber tracking from diffusionweighted MR data rely on a tensor model. However, the tensor model can only resolve a single fiber orient...
This paper investigates methods for clock skew minimization using buffer and wire sizing. First, a technique that significantly improves solution quality and stability of sequent...
Matthew R. Guthaus, Dennis Sylvester, Richard B. B...