Conjugate gradient methods form a class of iterative algorithms that are highly effective for solving large‐scale unconstrained optimisation problems. They achieve efficiency by constructing search ...

This is a preview. Log in through your library . Abstract A rate of convergence of the conjugate gradient method for minimizing the convex quadratic functionals in Hilbert space is investigated.

In this paper we test different conjugate gradient (CG) methods for solving largescale unconstrained optimization problems. The methods are divided in two groups: the first group includes five basic ...