X-Git-Url: http://gitweb.michael.orlitzky.com/?p=octave.git;a=blobdiff_plain;f=optimization%2Fconjugate_gradient_method.m;h=9b2ddac24377e5d02651f7b9e52a5ee3a4c0707c;hp=5b07e1c183f88f5f0764975a23edc1c27dad446e;hb=6e504c235e5e2ad1abc0a98b733ed2269936c17a;hpb=da77431bfbbb5fed8835d09aeea0de7eb7f6194a

diff --git a/optimization/conjugate_gradient_method.m b/optimization/conjugate_gradient_method.m
index 5b07e1c..9b2ddac 100644
--- a/optimization/conjugate_gradient_method.m
+++ b/optimization/conjugate_gradient_method.m
@@ -1,40 +1,40 @@
 function x_star = conjugate_gradient_method(A, b, x0, tolerance)
-  ##
-  ## Solve,
-  ##
-  ##   Ax = b
-  ##
-  ## or equivalently,
-  ##
-  ##   min [phi(x) = (1/2)*<Ax,x> + <b,x>]
-  ##
-  ## using Algorithm 5.2 in Nocedal and Wright.
-  ##
-  ## INPUT:
-  ##
-  ##   - ``A`` -- The coefficient matrix of the system to solve. Must
-  ##     be positive definite.
-  ##
-  ##   - ``b`` -- The right-hand-side of the system to solve.
-  ##
-  ##   - ``x0`` -- The starting point for the search.
-  ##
-  ##   - ``tolerance`` -- How close ``Ax`` has to be to ``b`` (in
-  ##     magnitude) before we stop.
-  ##
-  ## OUTPUT:
-  ##
-  ##   - ``x_star`` - The solution to Ax=b.
-  ##
-  ## NOTES:
-  ##
-  ## All vectors are assumed to be *column* vectors.
-  ##
+  %
+  % Solve,
+  %
+  %   Ax = b
+  %
+  % or equivalently,
+  %
+  %   min [phi(x) = (1/2)*<Ax,x> + <b,x>]
+  %
+  % using Algorithm 5.2 in Nocedal and Wright.
+  %
+  % INPUT:
+  %
+  %   - ``A`` -- The coefficient matrix of the system to solve. Must
+  %     be positive definite.
+  %
+  %   - ``b`` -- The right-hand-side of the system to solve.
+  %
+  %   - ``x0`` -- The starting point for the search.
+  %
+  %   - ``tolerance`` -- How close ``Ax`` has to be to ``b`` (in
+  %     magnitude) before we stop.
+  %
+  % OUTPUT:
+  %
+  %   - ``x_star`` - The solution to Ax=b.
+  %
+  % NOTES:
+  %
+  % All vectors are assumed to be *column* vectors.
+  %
   zero_vector = zeros(length(x0), 1);
 
   k = 0;
   xk = x0;
-  rk = A*xk - b; # The first residual must be computed the hard way.
+  rk = A*xk - b; % The first residual must be computed the hard way.
   pk = -rk;
 
   while (norm(rk) > tolerance)