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» Wavelet based preconditioners for sparse linear systems
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NIPS
1998
13 years 10 months ago
Modeling Surround Suppression in V1 Neurons with a Statistically Derived Normalization Model
We examine the statistics of natural monochromatic images decomposed using a multi-scale wavelet basis. Although the coefficients of this representation are nearly decorrelated, t...
Eero P. Simoncelli, Odelia Schwartz
ICPP
1990
IEEE
14 years 1 months ago
Reducing Memory and Traffic Requirements for Scalable Directory-Based Cache Coherence Schemes
As multiprocessors are scaled beyond single bus systems, there is renewed interest in directory-based cache coherence schemes. These schemes rely on a directory to keep track of a...
Anoop Gupta, Wolf-Dietrich Weber, Todd C. Mowry
EJASP
2010
89views more  EJASP 2010»
13 years 4 months ago
Sparsity-Aware Estimation of CDMA System Parameters
The number of active users, their timing offsets, and their (possibly dispersive) channels with the access point are decisive parameters for wireless code division multiple access...
Daniele Angelosante, Emanuele Grossi, Georgios B. ...
CORR
2010
Springer
97views Education» more  CORR 2010»
13 years 6 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
TSP
2010
13 years 3 months ago
Block-sparse signals: uncertainty relations and efficient recovery
We consider efficient methods for the recovery of block-sparse signals--i.e., sparse signals that have nonzero entries occurring in clusters--from an underdetermined system of line...
Yonina C. Eldar, Patrick Kuppinger, Helmut Bö...