Work

An improved LS-RMIL-type conjugate gradient projection algorithm for systems of nonlinear equations and impulse noise image restoration

Year: 2025

Type: article

Abstract: This paper proposes an improved LS-RMIL-type conjugate gradient projection algorithm designed for solving systems of nonlinear equations with convex constraints. The algorithm introduces a search direction that maintains sufficient descent and trust-region properties independent of the line search approach. It operates under relatively mild conditions, requiring only continuity and monotonicity of nonlinear equations, thus avoiding the need for stronger assumptions such as Lipschitz continuity. The global convergence of the algorithm is established under these relaxed conditions. Furthermore, numerical experiments demonstrate that the algorithm exhibits superior efficiency and stability, particularly in solving large-scale nonlinear systems and in applications such as impulse noise image restoration, outperforming existing methods.

Source: AIMS Mathematics

DOI: 10.3934/math.2025614

Authors: Yan Xia, Xuejie Ma, and Dandan Li

Institutions: Guangzhou Huashang College, Guangzhou Huashang Vocational College

Language: English

Topic: Iterative Methods for Nonlinear Equations

Subfield: Numerical Analysis

Field: Mathematics

Domain: Physical Sciences

Open Access status: gold

Estimated APC paid: $1,200

OpenAlex ID: W4411262286