jens
7b34529b24
git-svn-id: http://moon:8086/svn/matlab/trunk@91 801c6759-fa7c-4059-a304-17956f83a07c
40 lines
924 B
Matlab
40 lines
924 B
Matlab
function [d] = lbfgs(g,s,y,Hdiag)
|
|
% BFGS Search Direction
|
|
%
|
|
% This function returns the (L-BFGS) approximate inverse Hessian,
|
|
% multiplied by the gradient
|
|
%
|
|
% If you pass in all previous directions/sizes, it will be the same as full BFGS
|
|
% If you truncate to the k most recent directions/sizes, it will be L-BFGS
|
|
%
|
|
% s - previous search directions (p by k)
|
|
% y - previous step sizes (p by k)
|
|
% g - gradient (p by 1)
|
|
% Hdiag - value of initial Hessian diagonal elements (scalar)
|
|
|
|
[p,k] = size(s);
|
|
|
|
for i = 1:k
|
|
ro(i,1) = 1/(y(:,i)'*s(:,i));
|
|
end
|
|
|
|
q = zeros(p,k+1);
|
|
r = zeros(p,k+1);
|
|
al =zeros(k,1);
|
|
be =zeros(k,1);
|
|
|
|
q(:,k+1) = g;
|
|
|
|
for i = k:-1:1
|
|
al(i) = ro(i)*s(:,i)'*q(:,i+1);
|
|
q(:,i) = q(:,i+1)-al(i)*y(:,i);
|
|
end
|
|
|
|
% Multiply by Initial Hessian
|
|
r(:,1) = Hdiag*q(:,1);
|
|
|
|
for i = 1:k
|
|
be(i) = ro(i)*y(:,i)'*r(:,i);
|
|
r(:,i+1) = r(:,i) + s(:,i)*(al(i)-be(i));
|
|
end
|
|
d=r(:,k+1); |