Abstract:
Conjugate gradient (CG) methods are one of the most widely
used methods for solving nonlinear unconstrained
optimization problems, especially of large scale. That is, due
to their simplicity and low memory requirement. To analyze
the convergence properties of a CG method, it implemented
into two line searches; exact and inexact. In this paper, given
some data, some CG methods will be used to find a
polynomial function that fitting the data. To show the
efficiency, a comparison between CG methods and least
square method will be done.
