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» RLS-weighted Lasso for adaptive estimation of sparse signals
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TSP
2010
13 years 1 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
12 years 10 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
13 years 8 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»
13 years 6 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
14 years 8 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