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CORR
2011
Springer
282views Education» more  CORR 2011»
13 years 3 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
CORR
2008
Springer
178views Education» more  CORR 2008»
13 years 8 months ago
Model-Based Compressive Sensing
Compressive sensing (CS) is an alternative to Shannon/Nyquist sampling for acquisition of sparse or compressible signals that can be well approximated by just K N elements from a...
Richard G. Baraniuk, Volkan Cevher, Marco F. Duart...
ICASSP
2008
IEEE
14 years 3 months ago
A compressed sensing technique for OFDM channel estimation in mobile environments: Exploiting channel sparsity for reducing pilo
We consider the estimation of doubly selective wireless channels within pulse-shaping multicarrier systems (which include OFDM systems as a special case). A new channel estimation...
Georg Tauboeck, Franz Hlawatsch
SIAMIS
2010
129views more  SIAMIS 2010»
13 years 3 months ago
Compressed Remote Sensing of Sparse Objects
Abstract. The linear inverse source and scattering problems are studied from the perspective of compressed sensing, in particular the idea that sufficient incoherence and sparsity ...
Albert Fannjiang, Thomas Strohmer, Pengchong Yan
ICASSP
2011
IEEE
13 years 10 days ago
Sparsity-undersampling tradeoff of compressed sensing in the complex domain
In this paper, recently developed ONE-L1 algorithms for compressed sensing are applied to complex-valued signals and sampling matrices. The optimal and iterative solution of ONE-L...
Zai Yang, Cishen Zhang