My optimization problem is jointly convex for the positive values of the optimization variable. It comes as follows:
cvx_begin gp variable J1_part1 minimize(J1_part1*zigmabarlocalnormal(1,1) - J1_part1*matrix_frac(si,zigmabarlocalnormal(2:num,2:num)+J1_part1*constant*eye(num-1)) - log_det(J1_part1)); 1e-4<=J1_part1; cvx_end
Unfortunately, I confront with a disciplined convex programming error (MATRIX_FRAC is convex and nonmonotonic, so its input must be affine). I do not know how to rephrase the second term (out of three) of the optimization problem to be understandable by CVX. Could you please help me.
(The other variables which appear in the optimization problem are either constant scalars or constant matrices)