hello sir i want to calculate mean square error for my all possible value for the system how to calculate it ?
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k0=1;
ss=[0,1,2,3];
kk=0;
poss=[];
for ii=1:d
poss=[poss,k0+(ii-1)*(N/d)];
end
for ii=1:length(poss)
k1=poss(ii);
for jj=ii+1:length(poss)
k2=poss(jj);
kk=kk+1;
k_p(kk,:)=[k1,k2];
A=[1, 1 ; exp(1i*2*pi)*(k1-1)*(ss(2)/N), exp(1i*2*pi)*(k2-1)*(ss(2)/N) ;exp(1i*2*pi)*(k1-1)*(ss(3)/N) , exp(1i*2*pi)*(k2-1)*(ss(3)/N); exp(1i*2*pi)*(k1-1)*(ss(4)/N), exp(1i*2*pi)*(k2-1)*(ss(4)/N)];
XF=pinv(A)*XD(:,1)
1 commentaire
Walter Roberson
le 1 Avr 2016
Your code is not complete. Some end statements are missing.
What is the mean squared error to be calculated relative to? MSE is used for comparison between two things, not by itself.
What are the parts that are allowed to vary for consideration of "all possible values"? I see that d is not defined so should we take it that f is one of the things that can change?
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Image Analyst
le 1 Avr 2016
There is a function immse() in the Image Processing Toolbox. But like Walter says, you need two signals.
3 commentaires
Image Analyst
le 3 Avr 2016
That would be zero. The MSE of X as compared to X (itself) is, of course, zero.
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