Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.11851/6138
Title: A Recursive Way for Sparse Reconstruction of Parametric Spaces
Authors: Teke, Oğuzhan
Gürbüz, Ali Cafer
Arıkan, Orhan
Keywords: Compressive sensing
basis mismatch
off-grid targets
recursive solver
sparse reconstruction
Issue Date: 2014
Publisher: IEEE Computer Soc
Source: 48h Asilomar Conference on Signals, Systems and Computers -- NOV 02-05, 2014 -- Pacific Grove, CA
Series/Report no.: Conference Record of the Asilomar Conference on Signals Systems and Computers
Abstract: A novel recursive framework for sparse reconstruction of continuous parameter spaces is proposed by adaptive partitioning and discretization of the parameter space together with expectation maximization type iterations. Any sparse solver or reconstruction technique can be used within the proposed recursive framework. Experimental results show that proposed technique improves the parameter estimation performance of classical sparse solvers while achieving Cramer-Rao lower bound on the tested frequency estimation problem.
URI: https://hdl.handle.net/20.500.11851/6138
ISBN: 978-1-4799-8297-4
ISSN: 1058-6393
Appears in Collections:Elektrik ve Elektronik Mühendisliği Bölümü / Department of Electrical & Electronics Engineering
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection

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