Hello all.
I am a newbie at cvx and after reading through the guide I am still stumped. I have the following problem
variable H(n,n) hermitian semidefinite
minimize norm (diag([v])- BHH’*B)
where v is a vector of n numbers and B is an n\times n matrix. I keep getting a Disciplined convex programming error telling me that only scalar quadratic forms are allowed. As this is only one of the two terms of the real objective function i want to minimize (the other involves terms that are linear in H), i have tried several other small tricks (like declaring H^2 as my variable and using sqrtm(H) in the second term) but to no avail.
Can somebody help with how to properly define an objective function that uses a semidefinite Hermitian matrix and its complex conjugate?
Regards