150 search results - page 3 / 30 » Compressive sensing for sparsely excited speech signals |
ICASSP
2011
IEEE
12 years 9 months ago
2011
IEEE
The recently developed compressive sensing (CS) framework enables the design of sub-Nyquist analog-to-digital converters. Several architectures have been proposed for the acquisit...
ICASSP
2008
IEEE
13 years 11 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
12 years 9 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
2010
IEEE
13 years 5 months ago
2010
IEEE
In this paper we show that, surprisingly, it is possible to recover sparse signals from nonlinearly distorted measurements, even if the nonlinearity is unknown. Assuming just that...
ICASSP
2011
IEEE
12 years 9 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...