Sciweavers

JMLR
2012
12 years 1 months ago
Universal Measurement Bounds for Structured Sparse Signal Recovery
Standard compressive sensing results state that to exactly recover an s sparse signal in Rp , one requires O(s · log p) measurements. While this bound is extremely useful in prac...
Nikhil S. Rao, Ben Recht, Robert D. Nowak
TSP
2010
13 years 6 months ago
LS-CS-residual (LS-CS): compressive sensing on least squares residual
We consider the problem of recursively and causally reconstructing time sequences of sparse signals (with unknown and time-varying sparsity patterns) from a limited number of noisy...
Namrata Vaswani
MP
2002
103views more  MP 2002»
13 years 11 months ago
Detecting Jacobian sparsity patterns by Bayesian probing
In this paper we describe an automatic procedure for successively reducing the set of possible nonzeros in a Jacobian matrix until eventually the exact sparsity pattern is obtained...
Andreas Griewank, Christo Mitev
CORR
2007
Springer
110views Education» more  CORR 2007»
13 years 11 months ago
Information-theoretic limits on sparsity recovery in the high-dimensional and noisy setting
The problem of recovering the sparsity pattern of a fixed but unknown vector β∗ ∈ Rp based on a set of n noisy observations arises in a variety of settings, including subset...
Martin J. Wainwright
CORR
2010
Springer
207views Education» more  CORR 2010»
13 years 11 months ago
Collaborative Hierarchical Sparse Modeling
Sparse modeling is a powerful framework for data analysis and processing. Traditionally, encoding in this framework is performed by solving an 1-regularized linear regression prob...
Pablo Sprechmann, Ignacio Ramírez, Guillerm...
ICASSP
2010
IEEE
13 years 11 months ago
Wideband spectral estimation from compressed measurements exploiting spectral a priori information in Cognitive Radio systems
In Cognitive Radio scenarios channelization information from primary network may be available to the spectral monitor. Under this assumption we propose a spectral estimation algor...
Gonzalo Vazquez-Vilar, Roberto López-Valcar...
NIPS
2008
14 years 28 days ago
Resolution Limits of Sparse Coding in High Dimensions
This paper addresses the problem of sparsity pattern detection for unknown ksparse n-dimensional signals observed through m noisy, random linear measurements. Sparsity pattern rec...
Alyson K. Fletcher, Sundeep Rangan, Vivek K. Goyal
ICIP
2008
IEEE
15 years 1 months ago
Kalman filtered Compressed Sensing
We consider the problem of reconstructing time sequences of spatially sparse signals (with unknown and time-varying sparsity patterns) from a limited number of linear "incohe...
Namrata Vaswani