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TIT
2010
174views Education» more  TIT 2010»
13 years 29 days 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...
ICA
2007
Springer
14 years 12 days ago
Compressed Sensing and Source Separation
Abstract. Separation of underdetermined mixtures is an important problem in signal processing that has attracted a great deal of attention over the years. Prior knowledge is requir...
Thomas Blumensath, Mike E. Davies
ISSPIT
2010
13 years 1 months ago
On the use of compressive sampling for wide-band spectrum sensing
In a scenario where a cognitive radio unit wishes to transmit, it needs to know over which frequency bands it can operate. It can obtain this knowledge by estimating the power spe...
Dennis Sundman, Saikat Chatterjee, Mikael Skoglund
CORR
2011
Springer
214views Education» more  CORR 2011»
12 years 10 months ago
K-Median Clustering, Model-Based Compressive Sensing, and Sparse Recovery for Earth Mover Distance
We initiate the study of sparse recovery problems under the Earth-Mover Distance (EMD). Specifically, we design a distribution over m × n matrices A such that for any x, given A...
Piotr Indyk, Eric Price
ICIP
2010
IEEE
13 years 4 months ago
Compressed sensing of multiview images using disparity compensation
Compressed sensing is applied to multiview image sets and interimage disparity compensation is incorporated into image reconstruction in order to take advantage of the high degree...
Maria Trocan, Thomas Maugey, Eric W. Tramel, James...