A modified Liu-Storey scheme for nonlinear systems with an application to image recovery | ||
| Iranian Journal of Numerical Analysis and Optimization | ||
| مقاله 15، دوره 13، شماره 1 - شماره پیاپی 24، خرداد 2023، صفحه 38-58 اصل مقاله (978.3 K) | ||
| نوع مقاله: Research Article | ||
| شناسه دیجیتال (DOI): 10.22067/ijnao.2022.75413.1107 | ||
| نویسندگان | ||
| A.I. Kiri؛ M.Y. Waziri* ؛ K. Ahmed | ||
| Department of Mathematical Sciences, Bayero University, Kano, Nigeria. | ||
| چکیده | ||
| Like the Polak-Ribi`ere-Polyak (PRP) and Hestenes-Stiefel (HS) meth-ods, the classical Liu-Storey (LS) conjugate gradient scheme is widely be-lieved to perform well numerically. This is attributed to the in-built capa-bility of the method to conduct a restart when a bad direction is encoun-tered. However, the scheme’s inability to generate descent search direc-tions, which is vital for global convergence, represents its major shortfall. In this article, we present an LS-type scheme for solving system of mono-tone nonlinear equations with convex constraints. The scheme is based on the approach by Wang et al. (2020) and the projection scheme by Solodov and Svaiter (1998). The new scheme satisfies the important condition for global convergence and is suitable for non-smooth nonlinear problems. Fur-thermore, we demonstrate the method’s application in restoring blurry im-ages in compressed sensing. The scheme’s global convergence is established under mild assumptions and preliminary numerical results show that the proposed method is promising and performs better than two recent meth-ods in the literature. | ||
| کلیدواژهها | ||
| Nonlinear Monotone Equations؛ Line search؛ Projection method؛ Signal processing؛ Convex constraint؛ Image de-blurring | ||
| مراجع | ||
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