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A hybrid CG algorithm for nonlinear unconstrained optimization with application in image restoration | ||
| Journal of Mathematical Modeling | ||
| مقاله 8، دوره 12، شماره 2، مهر 2024، صفحه 301-317 اصل مقاله (7.88 M) | ||
| نوع مقاله: Research Article | ||
| شناسه دیجیتال (DOI): 10.22124/jmm.2024.26151.2317 | ||
| نویسندگان | ||
| Choubeila Souli1؛ Raouf Ziadi* 1؛ Abdelatif Bencherif-Madani1؛ Hisham Mohammed Khudhur2 | ||
| 1Laboratory of Fundamental and Numerical Mathematics (LMFN), University Ferhat Abbas Setif 1, Algeria | ||
| 2Department of Mathematics, College of Computer Science and Mathematics, University of Mosul, Mosul, Iraq | ||
| چکیده | ||
| This paper presents a new hybrid conjugate gradient method for solving nonlinear unconstrained optimization problems; it is based on a combination of $RMIL$ (Rivaie-Mustafa-Ismail-Leong) and $hSM$ (hybrid Sulaiman- Mohammed) methods. The proposed algorithm enjoys the sufficient descent condition without depending on any line search; moreover, it is globally convergent under the usual and strong Wolfe line search assumptions. The performance of the algorithm is demonstrated through numerical experiments on a set of 100 test functions from [1] and four image restoration problems with two noise levels. The numerical comparisons with four existing methods show that the proposed method is promising and effective. | ||
| کلیدواژهها | ||
| Unconstrained optimization؛ Hybrid conjugate gradient؛ Global convergence؛ Image restoration | ||
| مراجع | ||
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