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CORR
2011
Springer
282views Education» more  CORR 2011»
13 years 4 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
2012
Springer
218views Education» more  CORR 2012»
12 years 4 months ago
Robust 1-bit compressed sensing and sparse logistic regression: A convex programming approach
This paper develops theoretical results regarding noisy 1-bit compressed sensing and sparse binomial regression. We demonstrate that a single convex program gives an accurate estim...
Yaniv Plan, Roman Vershynin
TIT
2010
174views Education» more  TIT 2010»
13 years 3 months ago
Toeplitz Compressed Sensing Matrices With Applications to Sparse Channel Estimation
Compressed sensing (CS) has recently emerged as a powerful signal acquisition paradigm. In essence, CS enables the recovery of high-dimensional sparse signals from relatively few ...
Jarvis Haupt, Waheed Uz Zaman Bajwa, Gil M. Raz, R...
JDCTA
2010
188views more  JDCTA 2010»
13 years 3 months ago
Compressive Sensing Signal Detection Algorithm Based on Location Information of Sparse Coefficients
Without reconstructing the signal themselves, signal detection could be solved by detection algorithm, which directly processes sampling value obtained from compressive sensing si...
Bing Liu, Ping Fu, Shengwei Meng, Lunping Guo
ICASSP
2009
IEEE
14 years 3 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