I am finding a Cauchy point to minimize a quadratic problem using gradient projection method. And I get a trouble reading this equation.
$x(t) = x(t_{j−1}) + ∆t*p_{j−1}$ where $∆t=t_{j}-t_{j-1}$.
For example let us say that $t_{j-1}=0.0024$. Then what does $x(t_{j−1})=x(0.0024)$ mean and how do I compute it?