A hybrid CG algorithm for nonlinear unconstrained optimization with application in image restoration
Publish place: Journal of Mathematical Modeling، Vol: 12، Issue: 2
Publish Year: 1403
نوع سند: مقاله ژورنالی
زبان: English
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شناسه ملی سند علمی:
JR_JMMO-12-2_008
تاریخ نمایه سازی: 18 تیر 1403
Abstract:
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 ۱۰۰ test functions from [۱] 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.
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Authors
Choubeila Souli
Laboratory of Fundamental and Numerical Mathematics (LMFN), University Ferhat Abbas Setif ۱, Algeria
Raouf Ziadi
Laboratory of Fundamental and Numerical Mathematics (LMFN), University Ferhat Abbas Setif ۱, Algeria
Abdelatif Bencherif-Madani
Laboratory of Fundamental and Numerical Mathematics (LMFN), University Ferhat Abbas Setif ۱, Algeria
Hisham Khudhur
Department of Mathematics, College of Computer Science and Mathematics, University of Mosul, Mosul, Iraq