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ICASSP
2009
IEEE
15 years 10 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
117
Voted
ICASSP
2008
IEEE
15 years 10 months ago
Reconstructing sparse signals from their zero crossings
Classical sampling records the signal level at pre-determined time instances, usually uniformly spaced. An alternative implicit sampling model is to record the timing of pre-deter...
Petros Boufounos, Richard G. Baraniuk
ICASSP
2008
IEEE
15 years 10 months ago
Application of sparse signal recovery to pilot-assisted channel estimation
We examine the application of current research in sparse signal recovery to the problem of channel estimation. Specifically, using an Orthogonal Frequency Division Multiplexed (O...
Matthew Sharp, Anna Scaglione
138
Voted
ICASSP
2008
IEEE
15 years 10 months ago
Subspace compressive detection for sparse signals
The emerging theory of compressed sensing (CS) provides a universal signal detection approach for sparse signals at sub-Nyquist sampling rates. A small number of random projection...
Zhongmin Wang, Gonzalo R. Arce, Brian M. Sadler
ICIP
2007
IEEE
15 years 10 months ago
Sparse Gradient Image Reconstruction Done Faster
In a wide variety of imaging applications (especially medical imaging), we obtain a partial set or subset of the Fourier transform of an image. From these Fourier measurements, we...
Ray Maleh, Anna C. Gilbert, Martin J. Strauss