168 search results - page 4 / 34 » Bayesian Compressive Sensing for clustered sparse signals |
ICASSP
2009
IEEE
14 years 2 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 ...
ICASSP
2011
IEEE
12 years 11 months ago
2011
IEEE
Compressive sensing (CS) is a new approach for the acquisition and recovery of sparse signals that enables sampling rates significantly below the classical Nyquist rate. Based on...
TIP
2010
13 years 5 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 ...
ICASSP
2009
IEEE
14 years 2 months ago
2009
IEEE
This paper studies the feasibility and investigates various choices in the application of compressive sensing (CS) to object-based surveillance video coding. The residual object e...
CORR
2008
Springer
13 years 6 months ago
2008
Springer
Abstract--A traditional assumption underlying most data converters is that the signal should be sampled at a rate exceeding twice the highest frequency. This statement is based on ...