This paper develops a new class of algorithms for signal recovery in the distributed compressive sensing (DCS) framework. DCS exploits both intra-signal and inter-signal correlati...
Stephen R. Schnelle, Jason N. Laska, Chinmay Hegde...
: Recurrent neural networks possess interesting universal approximation capabilities, making them good candidates for time series modeling. Unfortunately, long term dependencies ar...
With the ever expanding Web and the information published on it, effective tools for managing such data and presenting information to users based on their needs are becoming nece...
This paper presents a new (geometrical) approach to the computation of polyhedral (robustly) positively invariant (PI) sets for general (possibly discontinuous) nonlinear discrete...
A. Alessio, Mircea Lazar, Alberto Bemporad, W. P. ...
Songbirds have been widely used as a model for studying neuronal circuits that relate to vocal learning and production. An important component of this research relies on quantitat...