搜索结果: 1-9 共查到“统计学 Compressed Sensing”相关记录9条 . 查询时间(0.058 秒)
We consider the problem of estimating a sparse signal from a set of quantized, Gaussian noise corrupted measurements, where each measurement corresponds to an interval of values. We give two methods f...
An analysis of block sampling strategies in compressed sensing
Compressed Sensing blocks of measurements sampling continuous trajectories exact recovery,ℓ 1 minimization.
2013/6/17
Compressed sensing (CS) is a theory which guarantees the exact recovery of sparse signals from a few number of linear projections. The sampling schemes suggested by current CS theories are often of li...
Weighted algorithms for compressed sensing and matrix completion
Compressed Sensing Weighted Basis-Pursuit Matrix Completion
2011/7/19
This paper is about iteratively reweighted basis-pursuit algorithms for compressed sensing and matrix completion problems. In a first part, we give a theoretical explanation of the fact that reweighte...
Limiting Laws of Coherence of Random Matrices with Applications to Testing Covariance Structure and Construction of Compressed Sensing Matrices
Chen-Stein method coherence compressed sensing matrix covariance struc-ture law of large numbers limiting distribution maxima moderate deviations mutual incoherence property random matrix sample correlation matrix
2011/3/21
Kernel density estimation (KDE) is a popular statistical technique for estimating the underlying density distribution with minimal assumptions. Although they can be shown to achieve asymptotic estimat...
Limiting Laws of Coherence of Random Matrices with Applications to Testing Covariance Structure and Construction of Compressed Sensing Matrices
Chen-Stein method coherence compressed sensing matrix covariance struc-ture law of large numbers limiting distribution maxima moderate deviations mutual incoherence property random matrix sample correlation matrix
2011/3/23
Testing covariance structure is of significant interest in many areas of statistical analysis and construction of compressed sensing matrices is an important problem in signal processing. Motivated b...
Feasibility and performances of compressed-sensing and sparse map-making with Herschel/PACS data
Instrumentation and Methods for Astrophysics (astro-ph.IM) Galaxy Astrophysics (astro-ph.GA) Applications (stat.AP)
2010/12/17
The Herschel Space Observatory of ESA was launched in May 2009 and is in operation since. From its distant orbit around L2 it needs to transmit a huge quantity of information through a very limited ba...
Compressed Sensing for Sparse Underwater Channel Estimation:Some Practical Considerations
Compressed Sensing Sparse Underwater Channel Estimation Practical Considerations
2010/3/10
We examine the use of a structured thresholding algorithm for sparse underwater channel estimation using compressed
sensing. This method shows some improvements over standard algorithms for sparse ch...
The dynamics of message passing on dense graphs,with applications to compressed sensing
message passing dense graphs compressed sensing
2010/3/9
Approximate message passing’ algorithms proved to be extremely effective in reconstructing
sparse signals from a small number of incoherent linear measurements. Extensive numerical
experiments furth...
On Low Rank Matrix Approximations with Applications to Synthesis Problem in Compressed Sensing
Low Rank Matrix Approximations Applications Synthesis Problem Compressed Sensing
2010/3/9
We consider the synthesis problem of Compressed Sensing –given s and an M×n
matrix A, extract from it an m × n submatrix Am, certified to be s-good, with m
as small as possible. Starting from the ve...