A hybrid simulated annealing thresholding algorithm for compressed sensing

In this paper we present a new hybrid simulated annealing thresholding (HSAT) algorithm which preserves the computational simplicity of thresholding algorithm but with the global convergence. We verify the convergence of the new hybrid simulated annealing thresholding algorithm and provide a series...

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Bibliographic Details
Published in:Signal processing Vol. 93; no. 6; pp. 1577 - 1585
Main Authors: Fengmin, Xu, Shanhe, Wang
Format: Journal Article
Language:English
Published: Elsevier B.V 01.06.2013
Subjects:
Algorithms
Compressed
Compressed sensing
Convergence
Image reconstruction
Iterative thresholding algorithm
Preserves
Signal processing
Simulated annealing
Solvers
Statistical regularization
Iterative thresholding algorithm
Statistical regularization
Compressed sensing
Simulated annealing
ISSN:0165-1684, 1872-7557
Online Access:Get full text
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Summary:In this paper we present a new hybrid simulated annealing thresholding (HSAT) algorithm which preserves the computational simplicity of thresholding algorithm but with the global convergence. We verify the convergence of the new hybrid simulated annealing thresholding algorithm and provide a series of experiments and applications to assess performance of the algorithm. The experiments and applications show that the proposed hybrid algorithm is global convergence and can be accepted as a solver for signal and image reconstruction problems. ► We propose a new hybrid simulated annealing thresholding algorithm. ► We verify the convergence of the algorithm. ► We provide a series of experiments of CS.
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ISSN:0165-1684
1872-7557
DOI:10.1016/j.sigpro.2012.10.019