An Inertial CGP‐Based Method With a Hybrid Conjugate Parameter for Solving Constrained Nonlinear Equations: Applications in Impulse Noise Image Recovery

ABSTRACT In this paper, we propose a novel conjugate parameter in the search direction by enhancing the modified Polak‐Ribiére‐Polayk and Hestenes‐Stiefel methods through the hybrid technique. The constructed search direction inherently satisfies both the sufficient descent and trust region properties without the need for any line search strategies. By integrating this direction with the inertial‐relaxed technique, we develop an inertial conjugate gradient projection (CGP)‐based method for solving constrained nonlinear equations. Theoretical analysis confirms that the proposed method guarantees global convergence without requiring a Lipschitz continuity assumption. Experimental results further demonstrate the effectiveness of the proposed method in solving large‐scale constrained nonlinear equations and impulse noise image recovery applications.

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Publication Details

Journal
Mathematical Methods in the Applied Sciences
Published
2026-04-06
DOI
https://doi.org/10.1002/mma.70727
Primary Topic
Image and Signal Denoising Methods
Type
article
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article

An Inertial CGP‐Based Method With a Hybrid Conjugate Parameter for Solving Constrained Nonlinear Equations: Applications in Impulse Noise Image Recovery

Dandan Li, S. Wang
Mathematical Methods in the Applied Sciences
Image and Signal Denoising Methods
article

An Inertial CGP‐Based Method With a Hybrid Conjugate Parameter for Solving Constrained Nonlinear Equations: Applications in Impulse Noise Image Recovery

Dandan Li, S. Wang
article en

Abstract

ABSTRACT In this paper, we propose a novel conjugate parameter in the search direction by enhancing the modified Polak‐Ribiére‐Polayk and Hestenes‐Stiefel methods through the hybrid technique. The constructed search direction inherently satisfies both the sufficient descent and trust region properties without the need for any line search strategies. By integrating this direction with the inertial‐relaxed technique, we develop an inertial conjugate gradient projection (CGP)‐based method for solving constrained nonlinear equations. Theoretical analysis confirms that the proposed method guarantees global convergence without requiring a Lipschitz continuity assumption. Experimental results further demonstrate the effectiveness of the proposed method in solving large‐scale constrained nonlinear equations and impulse noise image recovery applications.

Mathematical Methods in the Applied Sciences
Guangzhou Automobile Group (China) (CN), Baise University (CN)
Openalex Percentile: Top 24%
Image and Signal Denoising Methods
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