In this paper, we present a resource conscious dynamic scheduling strategy for handling large volume computationally intensive loads in a Grid system involving multiple sources an...
We present two new hyperbolic source probability models to effectively represent sub-gaussian and super-gaussian families of sources for dynamic and convolutive Blind Source Recov...
This paper presents two algorithms, non-linear regression and Kalman filtering, that fuse heterogeneous data (pseudorange and angle-of-arrival) from an ultra-wideband positioning ...
— For the optimal approximation of multivariate Gaussian densities by means of Dirac mixtures, i.e., by means of a sum of weighted Dirac distributions on a continuous domain, a n...
We have previously proposed a trajectory model which is based on a mixture density network (MDN) trained with target variables augmented with dynamic features together with an algo...