Spectral conjugate gradient techniques for unconstrained optimization are frequently utilized
especially when the dimension is high. Based on the curvature information, updated spectral …

The quasi-Newton methods is an effective and interesting methods and their good accuracy
for unconstrained optimization. In this paper, a novel quasi-Newton equation is given based …

Quasi-Newton methods (QN) are very useful in finding the optimal solution to the
unconstrained optimization problems. The updated Hessian approximations fulfill the …

A variety of conjugate gradient algorithms are constructed on the coefficient conjugate. In
this paper, a new coefficient conjugate based on the quadratic model for impulse noise …

The formula conjugate is usually the focal point in conjugate gradient techniques. In this
paper, the Perry's conjugacy condition and quadratic model are used to derive a new …

The conjugate coefficient optimal is the very establishment of a variety of conjugate gradient
methods. This paper proposes a new class coefficient of conjugate gradient (CG) methods …

The conjugate gradient approach is used to resolve unrestricted optimization problems,
uses the quadratic model for the objective function to generate a new coefficient conjugate …

Quasi-Newton equations play a central role in quasi-Newton methods for optimization and
various quasi-Newton equations are available. The objective function's third-order Taylor …

Conjugate gradient methods are considered one of the most important famous methods for
solving unconstraint optimization problems; in addition to that they can be applied in …

Conjugate gradient methods are one of the most common iterative mathematical techniques
of their usefulness in optimizing linear and non-linear systems. In this paper, a new …