81 search results - page 5 / 17 » Reconstruction of sparse signals from distorted randomized m... |
IEEECGIV
2009
IEEE
14 years 2 months ago
2009
IEEE
The theory of compressive sampling involves making random linear projections of a signal. Provided signal is sparse in some basis, small number of such measurements preserves the ...
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 ...
ICIP
2008
IEEE
14 years 9 months ago
2008
IEEE
Previous compressive sensing papers have considered the example of recovering an image with sparse gradient from a surprisingly small number of samples of its Fourier transform. T...
TIT
2010
13 years 2 months ago
2010
In [12] the authors proved an asymptotic sampling theorem for sparse signals, showing that n random measurements permit to reconstruct an N-vector having k nonzeros provided n >...
CORR
2006
Springer
13 years 7 months ago
2006
Springer
We investigate the optimal performance of dense sensor networks by studying the joint source-channel coding problem. The overall goal of the sensor network is to take measurements ...