Hi, I am trying to use cvx instead of Yalmip for solving my LMI problem. I have my opt problem formulated in yalmip as follows:

```
X = sdpvar(n,n);
L = sdpvar(1,n,'full' );
mat = [X [A*X - B*L;L;X]';[A*X - B*L;L;X] blkdiag(X,inv(R),inv(Qx))]
optimize(mat >= 0, -trace(X))
K_f = value(L)*inv(value(X))
```

However, when I code it in cvx the K_cvx obtained is not the same as K_f.

```
cvx_begin
variable X(n,n)
variable L(1,n)
minimize (-trace(X))
subject to
[X [A*X-B*L ; L; X]';[A*X-B*L ; L; X] blkdiag(X,inv(R),inv(Qx))] >= 0
cvx_end
K_cvx = L*inv(X)
```

The code is quite simple, so I guess they are equivalent, but there is something wrong. Do you have any hints?