26 search results - page 4 / 6 » Universal Measurement Bounds for Structured Sparse Signal Re... |
BIOCOMP
2006
13 years 9 months ago
2006
Abstract-- The inference of a network structure from experimental data providing dynamical information about the underlying system of investigation is an important and still outsta...
TIT
2010
13 years 2 months ago
2010
In this paper, we study the number of measurements required to recover a sparse signal in M with L nonzero coefficients from compressed samples in the presence of noise. We conside...
CDC
2010
IEEE
13 years 2 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
2011
Springer
12 years 11 months ago
2011
Springer
—This paper addresses the problem of simultaneous signal recovery and dictionary learning based on compressive measurements. Multiple signals are analyzed jointly, with multiple ...
CISS
2011
IEEE
12 years 11 months ago
2011
IEEE
—In compressive sensing (CS), the Restricted Isometry Property (RIP) is a powerful condition on measurement operators which ensures robust recovery of sparse vectors is possible ...