An improved formula for conjugate gradient methods that reduces noise from images and solved unconstrained optimisation problems

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An improved conjugate gradient formula effectively reduces image noise and solves unconstrained optimization problems. Novelty: ClaimNovelty.METHODOLOGICAL. Consensus alignment: ConsensusAlignment.NEUTRAL.

Isam H. Halil; Hisham M. Khudhur

doi:10.1504/ijmmno.2027.10079953

July 15, 2026International Journal of Mathematical Modelling and Numerical Optimisation

An improved formula for conjugate gradient methods that reduces noise from images and solved unconstrained optimisation problems

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Key Points

To enhance conjugate gradient methods for better noise reduction in images and efficacy in unconstrained optimization problems.
Developed a new formula for conjugate gradient methods.
Applied the improved methods to image processing and various optimization challenges.
Evaluated performance through comparative analysis with traditional methods.
Achieved a significant reduction in noise levels in processed images (% reduction not specified).
Improved solution accuracy in unconstrained optimization problems compared to standard conjugate gradient methods.

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Implication

Demonstrates noise reduction in image processing and optimization, suggesting effective solutions.

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Cite This Study

Halil et al. (2026) studied this question.

synapsesocial.com/papers/6a59c6b8a58755010b471d81 https://doi.org/10.1504/ijmmno.2027.10079953

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An improved formula for conjugate gradient methods that reduces noise from images and solved unconstrained optimisation problems

Key Points

Ask about this paper

Implication

Abstract

Discussion

Cite This Study

An improved formula for conjugate gradient methods that reduces noise from images and solved unconstrained optimisation problems

Key Points

Ask about this paper

Implication

Abstract

Discussion

Cite This Study

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