*Here is my code:
variables Wc(n,n) symmetric
for i = 1:n
for j = 1:n
if(i ~= j)
Z(i,j) == 0;
Z(i,j) >= 0;
Z(i,j) <= 1;
sum(trace(Z)) == k;
Wc == semidefinite(n);
A * Wc + Wc * A’ + V * Z * V’ == 0;
%% The Cost Function which needs to be Maximized
with A being a random stable square matrix. I get this error message:
Error using det_rootn (line 28)
Matrix input 1 expected to be symmetric (deviation: 2).
— If this number is small (<1e-6), it may simply be due to roundoff error.
This can be corrected by applying the SYM(X) function.
— Otherwise, this is likely due to a modeling error. Did you declare the
relevant matrix variables to be “symmetric” or “hermitian”?
Error in log_det (line 27)
Error in ConvexRelaxation (line 33)
The matrix Wc is declared to be symmetric. can anybody help me figure out how to solve this problem.