diff --git a/matlab/rand_matrix_normal.m b/matlab/rand_matrix_normal.m
index e20dc92b8..63e661d45 100644
--- a/matlab/rand_matrix_normal.m
+++ b/matlab/rand_matrix_normal.m
@@ -1,23 +1,28 @@
 function B = rand_matrix_normal(n, p, M, Omega_lower_chol, Sigma_lower_chol)
-% rand_matrix_normal  Pseudo random matrices drawn from a
-%                     matrix-normal distribution
-%
-% B = rand_matrix_normal(n, p, M, Omega_lower_chol, Sigma_lower_chol)
-%
-% Returns an n-by-p matrix drawn from a Matrix-normal distribution
-%
-% B ~ MN_n*p(M, Omega, Sigma)   
-%
+
+% function B = rand_matrix_normal(n, p, M, Omega_lower_chol, Sigma_lower_chol)
+% Pseudo random matrices drawn from a matrix-normal distribution
+% B ~ MN_n*p(M, Omega, Sigma) 
 % Equivalent to vec(B) ~ N(vec(Mu), kron(Omega, Sigma))
 %
-% Same notations than: http://en.wikipedia.org/wiki/Matrix_normal_distribution
-%
-% M is the mean, n-by-p matrix
-% Omega_lower_chol is p-by-p, lower Cholesky decomposition of Omega
-% (Omega_lower_chol = chol(Omega, 'lower'))
-% Sigma_lower_chol is n-by-n, lower Cholesky decomposition of Sigma
-% (Sigma_lower_chol = chol(Sigma, 'lower'))
-    
+% INPUTS
+%    n:                 row
+%    p:                 column
+%    M:                 (n*p) matrix, mean
+%    Omega_lower_chol:  (p*p), lower Cholesky decomposition of Omega,
+%                       (Omega_lower_chol = chol(Omega, 'lower'))
+%    Sigma_lower_chol:  (n*n), lower Cholesky decomposition of Sigma,
+%                       (Sigma_lower_chol = chol(Sigma, 'lower'))
+%    
+% OUTPUTS
+%    B:                 (n*p) matrix drawn from a Matrix-normal distribution
+%        
+% SPECIAL REQUIREMENTS
+%    Same notations than: http://en.wikipedia.org/wiki/Matrix_normal_distribution
+%  
+% part of DYNARE, copyright Dynare Team (2003-2008)
+% Gnu Public License.
+
     B1 = randn(n * p, 1);
     B2 = kron(Omega_lower_chol, Sigma_lower_chol) * B1;
     B3 = reshape(B2, n, p);