A novel hybrid conjugate gradient algorithm constructed from multiple methods

Abstract

This work presents a study of the Conjugate Gradient method for solving large, sparse systems of linear equations. The method relies on constructing a sequence of conjugate directions and determining optimal step sizes to efficiently minimize the associated quadratic function. Its main numerical properties, including convergence behavior and computational efficiency, are examined and discussed.