Abstract
In this paper, a hybrid derivative-free conjugate gradient method that inherits the structures of two conjugate gradient methods is introduced to recover sparse signal in compressive sensing by solving the nonlinear convex constrained equations. The global convergence of the proposed method is proved, under some appropriate assumptions. Numerical experiments and comparisons suggest that the proposed algorithm is an efficient approach for sparse signal and image reconstruction in compressive sensing.
| Original language | English |
|---|---|
| Pages (from-to) | 2301-2320 |
| Number of pages | 20 |
| Journal | Journal of Interdisciplinary Mathematics |
| Volume | 25 |
| Issue number | 8 |
| DOIs | |
| State | Published - 2022 |
| Externally published | Yes |
Bibliographical note
Publisher Copyright:© 2022 Taru Publications.
Keywords
- 65K05
- 90C52
- 90C56
- 94A08
- Compressive sensing
- Conjugate gradient method
- Convex constraints
- Nonlinear equations
- Projection method
ASJC Scopus subject areas
- Analysis
- Applied Mathematics
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