TIT
2010
13 years 6 months ago
2010
The joint-sparse recovery problem aims to recover, from sets of compressed measurements, unknown sparse matrices with nonzero entries restricted to a subset of rows. This is an ex...
TC
2010
13 years 6 months ago
2010
Multithreaded architectures are becoming more and more popular. In order to evaluate their behavior, several methodologies and metrics have been proposed. A methodology defines whe...
SOCO
2010
Springer
13 years 6 months ago
2010
Springer
Until recently, local governments in Spain were using machines with rolling cylinders for verifying taximeters. However, the condition of the tires can lead to errors in the proces...
MVA
2010
13 years 6 months ago
2010
3D vision guided manipulation of components is a key problem of industrial machine vision. In this paper, we focus on the localization and pose estimation of known industrial objec...
CORR
2011
Springer
13 years 6 months ago
2011
Springer
The Compressive Sensing (CS) framework aims to ease the burden on analog-to-digital converters (ADCs) by reducing the sampling rate required to acquire and stably recover sparse s...
CDC
2010
IEEE
13 years 6 months ago
2010
IEEE
Abstract-- Recovering or estimating the initial state of a highdimensional system can require a potentially large number of measurements. In this paper, we explain how this burden ...
CORR
2010
Springer
13 years 9 months ago
2010
Springer
We study the calibration problem in circular ultrasound tomography devices for breast imaging, where the sensor positions deviate from the circumference of a perfect circle. We in...
ICRA
2009
IEEE
13 years 9 months ago
2009
IEEE
Abstract-- In this paper, we consider the problem of mobile robots navigating in environments with non-rigid objects. Whereas robots can plan their paths more effectively when they...
ICC
2009
IEEE
13 years 9 months ago
2009
IEEE
We consider the case when K sensors have strongly correlated measurements - they all observe a 0 or they all observe
ICASSP
2009
IEEE
13 years 9 months ago
2009
IEEE
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...