In this paper, we consider a class of sensor networks where the data is not required in real-time by an observer; for example, a sensor network monitoring a scientific phenomenon ...
Sameer Tilak, Nael B. Abu-Ghazaleh, Wendi Rabiner ...
Abstract. Compressive sensing (CS) is an emerging field that provides a framework for image recovery using sub-Nyquist sampling rates. The CS theory shows that a signal can be reco...
Volkan Cevher, Aswin C. Sankaranarayanan, Marco F....
We introduce a computational model of sensor fusion based on the topographic representations of a ”two-microphone and one camera” configuration. Our aim is to perform a robust...
This paper presents a general learning framework for non-rigid registration of MR brain images. Given a set of training MR brain images, three major types of information are partic...
This paper deals with the on-line carrier phase estimation in a digital receiver. We consider a Brownian phase evolution in a Data Aided scenario. The proposed study uses an overs...