MATLAB: Related to mutual information

MATLABmatlab function

This is a function for mutual information

function I = MutualInformation(X,Y);
if (size(X,2) > 1)  % More than one predictor?
    % Axiom of information theory

    I = JointEntropy(X) + Entropy(Y) - JointEntropy([X Y]);
else
    % Axiom of information theory
    I = Entropy(X) + Entropy(Y) - JointEntropy([X Y]);
end

But while running it is showing "not enough input arguements". I am not getting the problem. Can anyone please help me?

Best Answer

You need to go to the command line and call the routine, such as

   MutualInformation(rand(5,7), rand(5, 14))

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I think I know why you are getting 0.25 instead of 1.00 for the magnitudes. There are two separate reasons, each one of which is causing an error by a factor of 2x in the scaling, for a total error of 4x.

The first error is that you are looking at only half of the spectrum (the positive frequencies). You are "throwing away" the negative frequencies, which is fine, but if you want to have the "correct" magnitude, you have to adjust for that fact by multiplying the spectrum by a factor of 2.

The second is more subtle, and perhaps speculative on my part. The vector tri is a linear function that represents a triangular window that goes from a value of 1 on the left-hand-side of the axis to a value of 0 on the right-hand side. Since it is a triangle, it is easy to see that the average value of this triangular window is exactly 0.5. So, by multiplying the source signal by this trangular window, you have effectively cut the average amplitude by 0.5. As a result, the magnitude of the spectral lines will also be 1/2 of what they would otherwise be. So here again, you have to multiply the spectrum by another factor of 2 in order to adjust for this effect.

So I think the correct scaling would be:

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Does that make sense?

Rick

MATLAB: FFT of signal from text file

I don’t see the error in your code, but the code here I wrote (plotting half of the fft) works:

fidi = fopen('John Smith emg.txt', 'rt');
T_EMG = textscan(fidi, '%f%f', 'Delimiter',' ');
t = T_EMG{1};
EMG = T_EMG{2};
L = length(t);
Ts = mean(diff(t));                                 % Sampling Time
Fs = 1/Ts;                                          % Sampling Frequency
Fn = Fs/2;                                          % Nyquist Frequency
FEMG = fft(EMG)*2/L;                                % Fourier Transform (Normalised)
Fv = linspace(0, 1, fix(L/2)+1)*Fn;                 % Frequency Vector
Iv = 1:length(Fv);                                  % Index Vector
figure(1)
plot(Fv, abs(FEMG(Iv)))
grid

Best Answer

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MATLAB: FFT of signal from text file

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