Variables

provide

$\Vert .\Vert$

The standard for any vector

$\epsilon$

Small positive value

x

Local minimum point of function $f\left(x\right)$

${\lambda }_k$

Positive parameter to minimize the function $f\left(x\right)$

$\nabla$

Directional derivative

G

Gradient vector of pattern $n\times 1$

G_k

Hessian matrix $n\times n$

d_k

Vector search pattern $n\times 1$

f

Target function

y_k

Vector is the difference between two consecutive gradients of the pattern $n\times 1$