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NEW CONJUGATE GRADIENT METHODS APPLIED TO FUNCTION MINIMIZATION AND IMAGE RESTORATION | ||
| Computational Methods for Differential Equations | ||
| مقالات آماده انتشار، پذیرفته شده، انتشار آنلاین از تاریخ 28 شهریور 1405 اصل مقاله (1.24 M) | ||
| نوع مقاله: Research Paper | ||
| شناسه دیجیتال (DOI): 10.22034/cmde.2026.74268.3838 | ||
| نویسندگان | ||
| Yeldez J. Subhi1؛ Layla Hadi Jwear2؛ Basim A. Hassan* 3 | ||
| 1Department of Renewable Energy Techniques Engineering, College of Oil and Gas Techniques Engineering, Northern Technical University, Iraq. | ||
| 2Department of Family and Community Medicine, College of Medicine, University of Mosul, Iraq. | ||
| 3Department of Mathematics, College of Computers Sciences and Mathematics, University of Mosul, Iraq. | ||
| چکیده | ||
| Conjugate gradient methods have been extensively utilized as frameworks for tackling minimization problems and image recovery. Traditional methods employ the gradient of the objective function to establish search vectors. This paper introduces conjugate gradient techniques that primarily incorporate insights from the Golden Ratio (0.618). We demonstrated their global convergence and conducted numerical comparisons with well-known methods. The findings indicate that one of our proposed methods achieves performance comparable to the most effective traditional approach using the Fletcher and Reeves formula, with minor adjustments to the search direction. | ||
| کلیدواژه‌ها | ||
| Conjugate gradient methods؛ APPLIED TO FUNCTION MINIMIZATION؛ APPLIED TO IMAGE RESTORATION | ||
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آمار تعداد مشاهده مقاله: 50 تعداد دریافت فایل اصل مقاله: 53 |
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