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» Recovery of Sparsely Corrupted Signals
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CORR
2010
Springer
116views Education» more  CORR 2010»
13 years 7 months ago
Restricted Isometries for Partial Random Circulant Matrices
In the theory of compressed sensing, restricted isometry analysis has become a standard tool for studying how efficiently a measurement matrix acquires information about sparse an...
Holger Rauhut, Justin K. Romberg, Joel A. Tropp
IJDSN
2006
109views more  IJDSN 2006»
13 years 7 months ago
Infuse: A TDMA Based Data Dissemination Protocol for Sensor Networks
Reliable dissemination of bulk data is one of the important problems in sensor networks. For example, programming or upgrading the software in sensors at run-time requires reliabl...
Sandeep S. Kulkarni, Mahesh Arumugam
TIP
2011
123views more  TIP 2011»
13 years 2 months ago
Spatial Sparsity-Induced Prediction (SIP) for Images and Video: A Simple Way to Reject Structured Interference
We propose a prediction technique that is geared toward forming successful estimates of a signal based on a correlated anchor signal that is contaminated with complex interference...
Gang Hua, Onur G. Guleryuz
ICASSP
2008
IEEE
14 years 1 months ago
Time-frequency localization from sparsity constraints
In the case of multicomponent AM-FM signals, the idealized representation which consists of weighted trajectories on the time-frequency (TF) plane, is intrinsically sparse. Recent...
Pierre Borgnat, Patrick Flandrin
ICIP
2008
IEEE
14 years 1 months ago
Compressed sensing for multi-view tracking and 3-D voxel reconstruction
Compressed sensing(CS) suggests that a signal, sparse in some basis, can be recovered from a small number of random projections. In this paper, we apply the CS theory on sparse ba...
Dikpal Reddy, Aswin C. Sankaranarayanan, Volkan Ce...