Conjugate gradient methods are efficient for smooth optimization problems, while there are rare conjugate gradient based methods for solving a possibly nondifferentiable convex minimization problem. In this paper by making full use of inherent properties of Moreau-Yosida regularization and descent property of modified conjugate gradient method we propose a modified Fletcher-Reeves-type method f...

In this paper, by linearly combining the numerator and denominator terms of Dai-Liao (DL) Bamigbola-Ali-Nwaeze (BAN) conjugate gradient methods (CGMs), a general form DL-BAN method has been proposed. From form, new hybrid CGM, which was found to possess sufficient descent property is generated. Numerical experiment carried out on CGM in comparison with four existing CGMs, using some set large s...

The regularizing properties of the conjugate gradient iteration, applied to the normal equation of a linear ill-posed problem, were established by Nemirovskii in 1986. A seemingly more attractive variant of this algorithm is the minimal error method suggested by King. The present paper analyzes the regularizing properties of the minimal error method. It is shown that the discrepancy principle i...

Inspired by Tikhonov regularization, a non-linear conjugate gradient method is proposed with the purpose of simultaneously regularizing and solving the moment matrix equation. The procedure is based on a non-quadratic conjugate gradient algorithm with exact line search, restart and rescale. Applied to the problem of TM scattering by perfectly conducting rectangular cylinders, the method is show...

The performance of CGLS, a basic iterative method whose main idea is to organize the computation of conjugate gradient method applied to normal equations for solving least squares problems. On modern architecture is always limited because of the global communication required for inner products. Inner products often therefore present a bottleneck, and it is desirable to reduce or even eliminate ...