function [X]=gaus_mar(X0,rho,N)
% [X]=gaus_mar(X0,rho,N)
% GAUS_MAR generates a Gauss-Markov process of length N.
% The noise process is taken to be white Gaussian
% noise with zero mean and unit variance.
for i=1:2:N,
[Ws(i) Ws(i+1)]=gngauss; % Generate the noise process.
end;
X(1)=rho*X0+Ws(1); % first element in the Gauss--Markov process
for i=2:N,
X(i)=rho*X(i-1)+Ws(i); % the remaining elements
end;