A conjugate gradient projection method for solving equations with convex constraints

Li Zheng; Lei Yang; Yong Liang

doi:10.1016/j.cam.2020.112781

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A conjugate gradient projection method for solving equations with convex constraints

Li Zheng Lei Yang Yong Liang

Year: 2020 Journal: Journal of Computational and Applied Mathematics Vol: 375 Pages: 112781-112781 Publisher: Elsevier BV

DOI: 10.1016/j.cam.2020.112781

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Keywords:

Mathematics Lipschitz continuity Conjugate gradient method Projection method Monotonic function Line search Projection (relational algebra) Proximal Gradient Methods Iterative method Regular polygon Applied mathematics Nonlinear system Mathematical analysis Mathematical optimization Convex optimization Dykstra's projection algorithm Algorithm Geometry Computer science

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Advanced Optimization Algorithms Research

Physical Sciences → Mathematics → Numerical Analysis

Sparse and Compressive Sensing Techniques

Physical Sciences → Engineering → Computational Mechanics

Iterative Methods for Nonlinear Equations

Physical Sciences → Mathematics → Numerical Analysis

A conjugate gradient projection method for solving equations with convex constraints

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