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April 8, 2026Mathematical Methods in the Applied Sciences0 citations

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

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DLDandan LiSWS. Wang

Key Points

  • This research aims to develop a method using a hybrid conjugate parameter to solve constrained nonlinear equations and aid in image recovery from impulse noise.
  • Enhanced modified Polak-Ribiére-Polayk and Hestenes-Stiefel methods
  • Incorporation of inertial-relaxed technique
  • Development of an inertial conjugate gradient projection method
  • Theoretical analysis to confirm global convergence
  • Proposed method effectively solves large-scale constrained nonlinear equations
  • Demonstrated success in impulse noise image recovery
  • Guaranteed global convergence without requiring Lipschitz continuity

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.

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Cite This Study

Li et al. (2026) studied this question.

synapsesocial.com/papers/69d5f14b74eaea4b11a7adb0https://doi.org/10.1002/mma.70727
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