I’m trying to solve a problem by a special convex function define by myself.
The following is my code
cvx_begin
variable A(n,m)
minimize (trace(Y_2*(Y_2)’*A’*inv(M)*A))
subject to
for r=1:1:N
abs(A(r,r))==1;
end
But it pop up this error massage:
Only scalar quadratic forms can be specified in CVX
I can’t find out why, please help me.
Only scalar quadratic forms can be specified in CVX
Your objective function needs to evaluate to a real scalar. It appears to evaluate to a matrix, not a scalar.
Once you have an objective function which evaluate to a scalar, then it needs to be convex, and to be formulated in compliance with CVX’s DCP rules.
Given numerical values for all variables, if the objective function evaluates to 5, that is an example of a real scalar. if it evaluates to [8 2;2 1], which is a matrix, that is not a real scalar.
what should be done in this case?. I’m having a similar problem. how do solve my feasibility problem if my quadratic term is not scalar?
@Meghna_Singh if the above discussion does not adequately address your matter, you need to provide more information on your problem.
Perhaps you have specified this problem at How do I write this LMI constraint in cvx format? ? Or do you have another problem?