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Conjugate Gradient Hard Thresholding Pursuit Algorithm for Sparse Signal Recovery
- Source :
- Algorithms, Vol 12, Iss 2, p 36 (2019), Algorithms, Volume 12, Issue 2
- Publication Year :
- 2019
- Publisher :
- MDPI AG, 2019.
-
Abstract
- We propose a new iterative greedy algorithm to reconstruct sparse signals in Compressed Sensing. The algorithm, called Conjugate Gradient Hard Thresholding Pursuit (CGHTP), is a simple combination of Hard Thresholding Pursuit (HTP) and Conjugate Gradient Iterative Hard Thresholding (CGIHT). The conjugate gradient method with a fast asymptotic convergence rate is integrated into the HTP scheme that only uses simple line search, which accelerates the convergence of the iterative process. Moreover, an adaptive step size selection strategy, which constantly shrinks the step size until a convergence criterion is met, ensures that the algorithm has a stable and fast convergence rate without choosing step size. Finally, experiments on both Gaussian-signal and real-world images demonstrate the advantages of the proposed algorithm in convergence rate and reconstruction performance.
- Subjects :
- sparse recovery
lcsh:T55.4-60.8
Computer science
iterative algorithms
010103 numerical & computational mathematics
02 engineering and technology
01 natural sciences
lcsh:QA75.5-76.95
Theoretical Computer Science
Conjugate gradient method
Convergence (routing)
0202 electrical engineering, electronic engineering, information engineering
lcsh:Industrial engineering. Management engineering
0101 mathematics
Greedy algorithm
compressed sensing
Numerical Analysis
Iterative and incremental development
Line search
020206 networking & telecommunications
Thresholding
Computational Mathematics
Compressed sensing
Computational Theory and Mathematics
Rate of convergence
conjugate gradient
lcsh:Electronic computers. Computer science
Algorithm
Subjects
Details
- Language :
- English
- ISSN :
- 19994893
- Volume :
- 12
- Issue :
- 2
- Database :
- OpenAIRE
- Journal :
- Algorithms
- Accession number :
- edsair.doi.dedup.....a22bd65ea1a80de5aad94ce40c8563b5