bfgs.m

Calculates a BFGS approximation to the Newton-Raphson search direction for maximising a function using past gradients to build a serviceable substitute to a Hessian. Unlike LBFGS, the pseudo-Hessian matrix is formed explicitly.

Syntax

                    H=bfgs(dx_hist,dg_hist,g)

Parameters

   dx_hist  - history of x increments, a stack
              of column vectors, from the latest
              to the earliest

   dg_hist  - history of gradient increments,
              a stack of column vectors, from
              the latest to the earliest

   g        - current gradient (used for sizing)

Outputs

   H        - BFGS approximation to the Hessian
              matrix corresponding to the *nega-
              tive* Hessian of the objective.
              The corresponding ascent directi-
              on is obtained as:  direction=H\g

Examples

See examples in the Spinach distribution relevant to this function.

Notes

This page was generated from the function header in the Spinach repository.

See also

fmaxnewton.m, alpha_conds.m, bracketing.m, sectioning.m, cubic_interp.m, aux_mat.m, dirdiff.m, drifts.m, ensemble.m, hess_reorder.m, objeval.m, optimcon.m, trapdiff.m, Optimal_control_module

Version 2.11, authors: Ilya Kuprov