Matlab - Alguien me puede ayudar

Hola!!!
Necesito ayuda para hacer funcionar un programa en matlab. Es sobre el gradiente conjugado. Lo he encontrado en una pagina de internet se llama conj_grad.m(http://www2.imm.dtu.dk/~hbn/Software/#GO)
y no soy capaz de hacerlo funcionar. No creo que sea por la version (la que uso es la 6.1).
Si alguien sabe como hacerlo funcionar por favor que me ayude, porque yo no tengo ni idea y lo necesito para hacer un proyecto.
Adjunto aqui el codigo por si no quereis entrar ne la pagina:

function [X, info, perf] = conj_grad(fun,par, x0, opts)
%CONJ_GRAD Conjugate gradient method for nonlinear optimization:
% Find xm = argmin{f(x)} , where x is an n-vector and the scalar
% function f with gradient g (with elements g(i) = Df/Dx_i )
% must be given by a MATLAB function with with declaration
% function [f, g] = fun(x, par)
% par holds parameters of the function. It may be dummy.
%

% Call
% [X, info {, perf}] = conj_grad(fun,par, x0, opts)
%
% Input parameters
% fun : String with the name of the function.
% par : Parameters of the function. May be empty.
% x0 : Starting guess for x .
% opts : Vector with 9 elements:
% opts(1) : Choice of CG method:
% opts(1) = 1 : Fletcher - Reeves,
% otherwise : Polak - Ribiere
% opts(2) : Choice of line search method:
% opts(2) = 1 : Exact l. s., otherwise : Soft l.s.
% opts(3) : Upper bound on initial step
% opts(4:6) used in stopping criteria:
% ||g||_inf <= opts(4) or
% ||dx||_2 <= opts(5)*(opts(5) + ||x||_2) or
% no. of function evaluations exceeds opts(6) .
% opts(7:9) used as linesearch parameters lpar(3:5) .
% See LINESEARCH .
% Any illegal element in opts is replaced by its
% default value :
% opts(1:6) = [2 2 1 1e-4*||g(x0)||_inf 1e-6 100]
% and
% opts(2)=1: opts(7:9) = [1e-4 1e-6 10]
% opts(2)=2: opts(7:9) = [1e-1 1e-2 10]
%
% Output parameters
% X : If perf is present, then array, holding the iterates
% columnwise. Otherwise, computed solution vector.
% info : Performance information, vector with 6 elements:
% info(1:3) = final values of
% [f(x) ||g||_inf ||dx||_2]
% info(4:5) = no. of iteration steps and evaluations of (f,g)
% info(6) = 1 : Stopped by small gradient
% 2 : Stopped by small x-step
% 3 : Stopped by opts(6) .
% perf : (optional). If present, then array, holding
% perf(1:2,:) = values of f(x) and ||g||_inf
% perf(3:5,:) = Line search info: values of
% alpha, phi'(alpha), no. fct. evals.
%
% Use of other MATLAB functions : LINESEARCH .
%
% Method
% See Chapter 4 in P.E. Frandsen, K. Jonasson, H.B. Nielsen,
% O. Tingleff: "Unconstrained Optimization", IMM, DTU. 1999.

% Hans Bruun Nielsen, IMM, DTU. 99.08.05-09 / 08.23 / 12.07

% Check call
[x n f g opts] = check(fun,par,x0,opts);
% Finish initialization
k = 1; kmax = opts(6);
ng = norm(g, inf); n2g = norm(g); gg = n2g^2;
gam = 0; h = zeros(size(x)); nh = 0; neval = 1;
Trace = nargout > 2;
if Trace
X = x(:)*ones(1,kmax+1);
perf = [f; ng; zeros(3,1)]*ones(1,kmax+1);
end
found = ng <= opts(4);

while ~found
% Previous values
hpr = h; nhpr = nh; ggpr = gg;
if opts(1) == 2, gpr = g; end
% New direction and scaling
k = k+1; h = gam*h - g; nh = norm(h);
% Check descent
gh = dot(g,h);
if dot(g,h) >= -1e-3 * n2g * nh % Not descent
h = -g; nh = n2g;
end
% Scale, aiming at alpha = 1
if k > 2, sc = .9*alpha*nhpr/nh;
else % First step. Try not to move too far
sc = opts(3)/32/nh;
end
% Line search
lspar = [32 opts([2 7:8]) min(kmax-neval, opts(9))];
[al f g dval] = linesearch(fun,par,x,f,g, sc*h, lspar);
alpha = sc*al; ng = norm(g, inf); n2g = norm(g); gg = n2g^2;
% Update gamma and x
if opts(1) == 1, gam = gg/ggpr;
else, gam = dot(g-gpr,g)/ggpr; end
x = x + alpha*h; neval = neval + dval;
if Trace
X(:,k) = x(:); perf(1:2,k) = [f; ng];
perf(3:5,k-1) = [alpha; dot(h,g); dval]; end
% Check stopping criteria
if ng <= opts(4), found = 1;
elseif alpha*nh <= opts(5)*(opts(5) + norm(x)), found = 2;
elseif neval >= kmax, found = 3; end
end % iteration

% Set return values
if Trace
X = X(:,1:k); perf = perf(:,1:k);
else, X = x; end
info = [f ng alpha*nh k-1 neval found];

% ========== auxiliary function =================================

function [x,n, f,g, opts] = check(fun,par,x0,opts0)
% Check function call
sx = size(x0); n = max(sx);
if (min(sx) > 1)
error('x0 should be a vector'), end
x = x0; [f g] = feval(fun,x,par);
sf = size(f); sg = size(g);
if any(sf-1) | ~isreal(f)
error('f should be a real valued scalar'), end
if any(sg - sx)
error('g should be a vector of the same type as x'), end

so = size(opts0);
if (min(so) ~= 1) | (max(so) < 9) | any(~isreal(opts0(1:9)))
error('opts should be a real valued vector of length 9'), end
opts = opts0(1:9); opts = opts(:).';
i = find(opts(1:2) > 2);
if length(i) % Set default values
d = [2 2]; opts(i) = d(i);
end
i = find(opts(1:6) <= 0);
if length(i) % Set default values
d = [2 2 1 1e-4*norm(g, inf) 1e-6 100];
opts(i) = d(i);
end
i = find(opts(7:9) <= 0);
if length(i) % Set default values
d = [1e-6 1e-6 10; 1e-1 1e-2 10];
opts(6+i) = d(opts(2),i);
end