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ICASSP
2008
IEEE
14 years 4 months ago
2008
IEEE
Consider a scenario where a distributed signal is sparse and is acquired by various sensors that see different versions. Thus, we have a set of sparse signals with both some commo...
ICASSP
2011
IEEE
13 years 1 months ago
2011
IEEE
We introduce the Multiplicative Update Selector and Estimator (MUSE) algorithm for sparse approximation in underdetermined linear regression problems. Given f = Φα∗ + µ, the ...
ICASSP
2011
IEEE
13 years 1 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...
ICASSP
2009
IEEE
14 years 4 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 8 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 ...