An efficient gradient-based algorithm with descent direction for unconstrained optimization with applications to image restoration and robotic motion control
This study presents a novel gradient-based algorithm designed to enhance the performance of optimization models, particularly in computer science applications such as image restoration and robotic motion control. The proposed algorithm introduces a modified conjugate gradient (CG) method, ensuring t...
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| Format: | Article |
| Language: | English |
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PeerJ Inc.
2025-05-01
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| Series: | PeerJ Computer Science |
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| Online Access: | https://peerj.com/articles/cs-2783.pdf |
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| author | Sulaiman Mohammed Ibrahim Aliyu M. Awwal Maulana Malik Ruzelan Khalid Aida Mauziah Benjamin Mohd Kamal Mohd Nawawi Elissa Nadia Madi |
| author_facet | Sulaiman Mohammed Ibrahim Aliyu M. Awwal Maulana Malik Ruzelan Khalid Aida Mauziah Benjamin Mohd Kamal Mohd Nawawi Elissa Nadia Madi |
| author_sort | Sulaiman Mohammed Ibrahim |
| collection | DOAJ |
| description | This study presents a novel gradient-based algorithm designed to enhance the performance of optimization models, particularly in computer science applications such as image restoration and robotic motion control. The proposed algorithm introduces a modified conjugate gradient (CG) method, ensuring the CG coefficient, β κ, remains integral to the search direction, thereby maintaining the descent property under appropriate line search conditions. Leveraging the strong Wolfe conditions and assuming Lipschitz continuity, we establish the global convergence of the algorithm. Computational experiments demonstrate the algorithm’s superior performance across a range of test problems, including its ability to restore corrupted images with high precision and effectively manage motion control in a 3DOF robotic arm model. These results underscore the algorithm’s potential in addressing key challenges in image processing and robotics. |
| format | Article |
| id | doaj-art-deb19d5c732b4b92bd0237d6a1b0a59d |
| institution | Kabale University |
| issn | 2376-5992 |
| language | English |
| publishDate | 2025-05-01 |
| publisher | PeerJ Inc. |
| record_format | Article |
| series | PeerJ Computer Science |
| spelling | doaj-art-deb19d5c732b4b92bd0237d6a1b0a59d2025-08-20T03:54:11ZengPeerJ Inc.PeerJ Computer Science2376-59922025-05-0111e278310.7717/peerj-cs.2783An efficient gradient-based algorithm with descent direction for unconstrained optimization with applications to image restoration and robotic motion controlSulaiman Mohammed Ibrahim0Aliyu M. Awwal1Maulana Malik2Ruzelan Khalid3Aida Mauziah Benjamin4Mohd Kamal Mohd Nawawi5Elissa Nadia Madi6School of Quantitative Sciences, Universiti Utara Malaysia, Sintok, Kedah, MalaysiaDepartment of Mathematics, Gombe State University, Gombe, NigeriaDepartment of Mathematics, Faculty of Mathematics and Natural Sciences, Universitas Indonesia, Depok, IndonesiaSchool of Quantitative Sciences, Universiti Utara Malaysia, Sintok, Kedah, MalaysiaSchool of Quantitative Sciences, Universiti Utara Malaysia, Sintok, Kedah, MalaysiaSchool of Quantitative Sciences, Universiti Utara Malaysia, Sintok, Kedah, MalaysiaFaculty of Informatics and Computing, Universiti Sultan Zainal Abidin, Besut, Terengganu, NigeriaThis study presents a novel gradient-based algorithm designed to enhance the performance of optimization models, particularly in computer science applications such as image restoration and robotic motion control. The proposed algorithm introduces a modified conjugate gradient (CG) method, ensuring the CG coefficient, β κ, remains integral to the search direction, thereby maintaining the descent property under appropriate line search conditions. Leveraging the strong Wolfe conditions and assuming Lipschitz continuity, we establish the global convergence of the algorithm. Computational experiments demonstrate the algorithm’s superior performance across a range of test problems, including its ability to restore corrupted images with high precision and effectively manage motion control in a 3DOF robotic arm model. These results underscore the algorithm’s potential in addressing key challenges in image processing and robotics.https://peerj.com/articles/cs-2783.pdfGradient based methodImage restorationRobotic motion controlUnconstrained optimizationConvergence analysis |
| spellingShingle | Sulaiman Mohammed Ibrahim Aliyu M. Awwal Maulana Malik Ruzelan Khalid Aida Mauziah Benjamin Mohd Kamal Mohd Nawawi Elissa Nadia Madi An efficient gradient-based algorithm with descent direction for unconstrained optimization with applications to image restoration and robotic motion control PeerJ Computer Science Gradient based method Image restoration Robotic motion control Unconstrained optimization Convergence analysis |
| title | An efficient gradient-based algorithm with descent direction for unconstrained optimization with applications to image restoration and robotic motion control |
| title_full | An efficient gradient-based algorithm with descent direction for unconstrained optimization with applications to image restoration and robotic motion control |
| title_fullStr | An efficient gradient-based algorithm with descent direction for unconstrained optimization with applications to image restoration and robotic motion control |
| title_full_unstemmed | An efficient gradient-based algorithm with descent direction for unconstrained optimization with applications to image restoration and robotic motion control |
| title_short | An efficient gradient-based algorithm with descent direction for unconstrained optimization with applications to image restoration and robotic motion control |
| title_sort | efficient gradient based algorithm with descent direction for unconstrained optimization with applications to image restoration and robotic motion control |
| topic | Gradient based method Image restoration Robotic motion control Unconstrained optimization Convergence analysis |
| url | https://peerj.com/articles/cs-2783.pdf |
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