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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irfan
am 1 Apr. 2016
Kommentiert: irfan
am 4 Apr. 2016
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 Kommentar
Walter Roberson
am 1 Apr. 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?
Akzeptierte Antwort
Image Analyst
am 1 Apr. 2016
There is a function immse() in the Image Processing Toolbox. But like Walter says, you need two signals.
3 Kommentare
Image Analyst
am 3 Apr. 2016
That would be zero. The MSE of X as compared to X (itself) is, of course, zero.
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