A Modified Conjugate Gradient Projection Method for Constrained Monotone Equations with Applications
Yaping Hu ()
Additional contact information
Yaping Hu: Tianjin University of Science and Technology
Journal of Optimization Theory and Applications, 2025, vol. 207, issue 3, No 14, 22 pages
Abstract:
Abstract This paper presents an enhanced Wei-Yao-Liu conjugate gradient projection algorithm, tailored for solving large-scale nonlinear convex constrained monotone equations. The algorithm’s search direction guarantees sufficient descent, while both the direction and line search are derivative-free, making it highly efficient for large-scale problems. We prove the algorithm’s global convergence under suitable assumptions and demonstrate its applicability to sparse signal reconstruction and blurry image recovery in compressive sensing. Numerical experiments validate the algorithm’s effectiveness, especially in large-scale scenarios, underscoring the advantages of its derivative-free design.
Keywords: Monotone equations; Convex constraint; Projection method; Signal reconstruction; Image recovery; 90C30; 90C26 (search for similar items in EconPapers)
Date: 2025
References: View complete reference list from CitEc
Citations:
Downloads: (external link)
http://link.springer.com/10.1007/s10957-025-02820-3 Abstract (text/html)
Access to the full text of the articles in this series is restricted.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:spr:joptap:v:207:y:2025:i:3:d:10.1007_s10957-025-02820-3
Ordering information: This journal article can be ordered from
http://www.springer. ... cs/journal/10957/PS2
DOI: 10.1007/s10957-025-02820-3
Access Statistics for this article
Journal of Optimization Theory and Applications is currently edited by Franco Giannessi and David G. Hull
More articles in Journal of Optimization Theory and Applications from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().