The recently developed compressive sensing (CS) framework enables the design of sub-Nyquist analog-to-digital converters. Several architectures have been proposed for the acquisit...
John P. Slavinsky, Jason N. Laska, Mark A. Davenpo...
This paper studies compressed sensing for the recovery of non-negative sparse vectors from a smaller number of measurements than the ambient dimension of the unknown vector. We fo...
Work in simultaneous localisation and map-building ("SLAM") for mobile robots has focused on the simplified case in which a robot is considered to move in two dimensions...
We propose a novel approach to the problem of simultaneous localization and mapping (SLAM) based on incremental smoothing, that is suitable for real-time applications in large-sca...
The advent of Compressive Sensing has provided significant mathematical tools to enhance the sensing capabilities of hardware devices. In this paper we apply Compressive Sensing ...