Sciweavers

150 search results - page 1 / 30
» Compressive sensing for sparsely excited speech signals
Sort
View
ICASSP
2009
IEEE
13 years 11 months ago
Compressive sensing for sparsely excited speech signals
Compressive sensing (CS) has been proposed for signals with sparsity in a linear transform domain. We explore a signal dependent unknown linear transform, namely the impulse respo...
Thippur V. Sreenivas, W. Bastiaan Kleijn
CORR
2011
Springer
282views Education» more  CORR 2011»
12 years 11 months ago
Fast Linearized Bregman Iteration for Compressive Sensing and Sparse Denoising
We propose and analyze an extremely fast, efficient and simple method for solving the problem: min{ u 1 :Au=f,u∈Rn }. This method was first described in [1], with more details i...
Stanley Osher, Yu Mao, Bin Dong, Wotao Yin
CISS
2010
IEEE
12 years 8 months ago
Average case analysis of sparse recovery from combined fusion frame measurements
—Sparse representations have emerged as a powerful tool in signal and information processing, culminated by the success of new acquisition and processing techniques such as Compr...
Petros Boufounos, Gitta Kutyniok, Holger Rauhut
ICASSP
2011
IEEE
12 years 8 months ago
Bayesian Compressive Sensing for clustered sparse signals
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. ...
Lei Yu, Hong Sun, Jean-Pierre Barbot, Gang Zheng
CISS
2008
IEEE
13 years 11 months ago
1-Bit compressive sensing
Abstract—Compressive sensing is a new signal acquisition technology with the potential to reduce the number of measurements required to acquire signals that are sparse or compres...
Petros Boufounos, Richard G. Baraniuk