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» RLS-weighted Lasso for adaptive estimation of sparse signals
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ICASSP
2011
IEEE
12 years 10 months ago
Denoising of image patches via sparse representations with learned statistical dependencies
We address the problem of denoising for image patches. The approach taken is based on Bayesian modeling of sparse representations, which takes into account dependencies between th...
Tomer Faktor, Yonina C. Eldar, Michael Elad
CORR
2010
Springer
210views Education» more  CORR 2010»
13 years 6 months ago
Exploiting Statistical Dependencies in Sparse Representations for Signal Recovery
Signal modeling lies at the core of numerous signal and image processing applications. A recent approach that has drawn considerable attention is sparse representation modeling, in...
Tomer Faktor, Yonina C. Eldar, Michael Elad
ICASSP
2011
IEEE
12 years 10 months ago
Acceleration of adaptive proximal forward-backward splitting method and its application to sparse system identification
In this paper, we propose an acceleration technique of the adaptive filtering scheme called adaptive proximal forward-backward splitting method. For accelerating the convergence ...
Masao Yamagishi, Masahiro Yukawa, Isao Yamada
ICASSP
2011
IEEE
12 years 10 months ago
Sparse channel estimation with lp-norm and reweighted l1-norm penalized least mean squares
The least mean squares (LMS) algorithm is one of the most popular recursive parameter estimation methods. In its standard form it does not take into account any special characteri...
Omid Taheri, Sergiy A. Vorobyov
PERCOM
2005
ACM
14 years 6 months ago
Adaptive Temporal Radio Maps for Indoor Location Estimation
In this paper, we present a novel method to adapt the temporal radio maps for indoor location determination by offsetting the variational environmental factors using data mining t...
Jie Yin, Qiang Yang, Lionel M. Ni