hello sir i want to calculate mean square error for my all possible value for the system how to calculate it ?
1 view (last 30 days)
Show older comments
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 Comment
Walter Roberson
on 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?
Accepted Answer
Image Analyst
on 1 Apr 2016
There is a function immse() in the Image Processing Toolbox. But like Walter says, you need two signals.
3 Comments
Image Analyst
on 3 Apr 2016
That would be zero. The MSE of X as compared to X (itself) is, of course, zero.
More Answers (0)
See Also
Categories
Find more on Signal Generation and Preprocessing in Help Center and File Exchange
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!