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FOCM
2010
82views more  FOCM 2010»
13 years 3 months ago
Stability and Instance Optimality for Gaussian Measurements in Compressed Sensing
In compressed sensing we seek to gain information about vector x ∈ RN from d << N nonadaptive linear measurements. Candes, Donoho, Tao et. al. ( see e.g. [2, 4, 8]) propos...
P. Wojtaszczyk
CORR
2008
Springer
98views Education» more  CORR 2008»
13 years 5 months ago
Sparse Recovery by Non-convex Optimization -- Instance Optimality
In this note, we address the theoretical properties of p, a class of compressed sensing decoders that rely on p minimization with p (0, 1) to recover estimates of sparse and compr...
Rayan Saab, Özgür Yilmaz
DCC
2010
IEEE
13 years 11 months ago
On the Systematic Measurement Matrix for Compressed Sensing in the Presence of Gross Errors
Inspired by syndrome source coding using linear error-correcting codes, we explore a new form of measurement matrix for compressed sensing. The proposed matrix is constructed in t...
Zhi Li, Feng Wu, John Wright
CORR
2010
Springer
97views Education» more  CORR 2010»
13 years 2 months ago
On the Scaling Law for Compressive Sensing and its Applications
1 minimization can be used to recover sufficiently sparse unknown signals from compressed linear measurements. In fact, exact thresholds on the sparsity, as a function of the ratio...
Weiyu Xu, Ao Tang
CORR
2011
Springer
210views Education» more  CORR 2011»
12 years 12 months ago
Statistical Compressed Sensing of Gaussian Mixture Models
A novel framework of compressed sensing, namely statistical compressed sensing (SCS), that aims at efficiently sampling a collection of signals that follow a statistical distribu...
Guoshen Yu, Guillermo Sapiro