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» RLS-weighted Lasso for adaptive estimation of sparse signals
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TSP
2010
14 years 4 months ago
Distributed spectrum sensing for cognitive radio networks by exploiting sparsity
Abstract--A cooperative approach to the sensing task of wireless cognitive radio (CR) networks is introduced based on a basis expansion model of the power spectral density (PSD) ma...
Juan Andrés Bazerque, Georgios B. Giannakis
ICASSP
2011
IEEE
14 years 1 months ago
A sliding-window online fast variational sparse Bayesian learning algorithm
In this work a new online learning algorithm that uses automatic relevance determination (ARD) is proposed for fast adaptive nonlinear filtering. A sequential decision rule for i...
Thomas Buchgraber, Dmitriy Shutin, H. Vincent Poor
ICA
2010
Springer
14 years 10 months ago
Blind Source Separation Based on Time-Frequency Sparseness in the Presence of Spatial Aliasing
In this paper, we propose a novel method for blind source separation (BSS) based on time-frequency sparseness (TF) that can estimate the number of sources and time-frequency masks,...
Benedikt Loesch, Bin Yang
TSP
2008
100views more  TSP 2008»
14 years 9 months ago
Optimal Two-Stage Search for Sparse Targets Using Convex Criteria
We consider the problem of estimating and detecting sparse signals over a large area of an image or other medium. We introduce a novel cost function that captures the tradeoff bet...
Eran Bashan, Raviv Raich, Alfred O. Hero III
ICIP
2006
IEEE
15 years 11 months ago
Robust Kernel Regression for Restoration and Reconstruction of Images from Sparse Noisy Data
We introduce a class of robust non-parametric estimation methods which are ideally suited for the reconstruction of signals and images from noise-corrupted or sparsely collected s...
Hiroyuki Takeda, Sina Farsiu, Peyman Milanfar