Archive | 2021
A Modified Conjugate Gradient Method for Solving Large-Scale Nonlinear Equations
Abstract
Solving nonlinear equations is an important problem which appears in various models of science and engineering such as computer vision, computational geometry, signal processing, computational chemistry, and robotics. More specifically, the subproblems in the generalized proximal algorithms with Bergman distances is a monotone nonlinear equations [1], and l1-norm regularized optimization problems can be reformulated as monotone nonlinear equations [2]. Due to its wide applications, the studies in the numerical methods for solving the monotone nonlinear equations have received much attention [3–10]. In this paper, we are interested in the numerical methods for solving monotone nonlinear equations with convex constraints: