Abstract
We propose an efficient three-term projection method for solving convex-constrained nonlinear monotone equations, with applications to sparse signal reconstruction problems, in this paper. The proposed algorithm has three main appealing features; it is a new variant of BFGS modification; it satisfies the famous D–L conjugacy condition, and it satisfies the sufficient descent condition. The global convergence of the proposed algorithm is proven under some suitable conditions. Numerical results presented display the efficacy of the proposed algorithm in comparison with existing algorithms. Finally, the proposed algorithm is used to solve the sparse signal reconstruction problem.
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Acknowledgements
The second author acknowledges with thanks, the Nonlinear Dynamics and Mathematical Application Center, Kyungpook National University, Republic of Korea for providing excellent research facilities and the Department of Mathematics and Applied Mathematics at the Sefako Makgatho Health Sciences University. The fourth author is grateful to the support of Bansomdejchaopraya Rajabhat University.
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Abdullahi, M., Abubakar, A.B., Sulaiman, A. et al. An efficient projection algorithm for solving convex constrained monotone operator equations and sparse signal reconstruction problems. J Anal (2024). https://doi.org/10.1007/s41478-024-00757-w
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DOI: https://doi.org/10.1007/s41478-024-00757-w
Keywords
- Signal reconstruction problem
- Convex constraints
- Projection map
- Monotone operator equation
- Global convergence