52 search results - page 1 / 11 » Bayesian Compressive Sensing Using Laplace Priors |
ICASSP
2009
IEEE
13 years 11 months ago
2009
IEEE
In this paper we model the components of the compressive sensing (CS) problem using the Bayesian framework by utilizing a hierarchical form of the Laplace prior to model sparsity ...
TIP
2010
13 years 2 months ago
2010
In this paper we model the components of the compressive sensing (CS) problem, i.e., the signal acquisition process, the unknown signal coefficients and the model parameters for ...
JMLR
2008
13 years 4 months ago
2008
The linear model with sparsity-favouring prior on the coefficients has important applications in many different domains. In machine learning, most methods to date search for maxim...
ICML
2008
IEEE
14 years 5 months ago
2008
IEEE
Compressive sensing (CS) is an emerging field that, under appropriate conditions, can significantly reduce the number of measurements required for a given signal. In many applicat...
ICASSP
2011
IEEE
12 years 8 months ago
2011
IEEE
In traditional framework of Compressive Sensing (CS), only sparse prior on the property of signals in time or frequency domain is adopted to guarantee the exact inverse recovery. ...