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.

Since every plane-harmonic function is associated with a conjugate, problems in which normal gradients are specified on the boundary can be transformed into problems in which boundary values are ...