I have a minimize problem and the cvx code is followed as:
cvx_begin variable x(n); for i = 1:c ee(i) = norm(T(:,:,i)*x-y,2)/norm(y,2); end minimize (norm(D*x-y,2)+0.01*sum(ee)); cvx_end
In the objective function, only x is variable and others are all known. n is the dimension of vector x and c is just a loop number less than 100. I am sorry I do not use other solvers to this problem but the cost time is unacceptable. Do you think there is no improvement space?
In my problem, the size of n is 700 and the size of y is a 300*1 vector. I have no idea why for this problem, CVX should cost so much time. How can i know the detailed optimization method which cvx used for my problem?
This code will cost 17 minutes to compute the result. It’s so slow and i don’t know how to speed up. Thank you very much!