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)
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
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?

Sign in to comment.

Accepted Answer

Image Analyst
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

Sign in to comment.

More Answers (0)

Categories

Find more on Signal Generation and Preprocessing in Help Center and File Exchange

Tags

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!