I would be grateful for some direction on this. I wish to implement the following - Given a deterministic signal (the feedback signal of a closed-loop stable system) I would like to plot the power spectral density. The definition I am working with is this: Implementation (MATLAB): % Given a signal the plot of the power spectral density over the frequency range 0.1-5 rad/s is given by % The continuous time fourier transform w=.1:.1:5; % 0.1 to 5 rad/s (frequency range of interest) % Compute the transform for ii=1:50 % For each frequency increment (50 samples over the interval 0.1:0.1:5) yy1=um.*sin(w(ii)*t) % where t is a vector of dimension [1, 3610] and um is the time series in question yy2=um.*cos(w(ii)*t) % % the intergral yi1=trapz(t,yy1); yi2=trapz(t,yy2); % square of the fourier transform i.e. |X(omega)|^2 trans(ii)=(yi1^2+yi2^2); end figure(1) plot(w, trans) % |X(omega)|^2 % For a deterministic signal no need to compute the expected value, the power of the signal is instead given by % Energy: integral of the square of the Fourier transform wrt to frequency energy = trapz(w, trans); figure(2) plot(w,energy) % sadly things have gone awry HERE! % Power power = energy / t(end); % where t(end) is the duration of the signal in question figure(3) plot(w, power) The PSD should be a real valued nonnegative function of omega not a constant. Any prompts would be much appreciated!