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- 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;