When I try to reproduce someone else’s paper， there is always many equality constraints. I know the CVX can well deal with the affine expressions.
pow_p({convex},2) is the wrong expression for CVX. So I add a variable m.
pow_p(m,2) is the correct expression. At the same time, we need to add an inequality constraint
{convex}<=m, then CVX can work. But some time, according to the actual situation， just have m={convex}, I would like to know if there is a way to solve this situation.
Thank you !
Nonlinear equality constraints are non-convex, and are not allowed by CVX.
Does this paper you are reproducing claim the problem you are trying to reproduce is a convex optimization problem?
Thank you for your reply sincerely. Excuse me， I still have some questions.
v[n] is a vector. norm{v[n]}^3 should be a convex expression in the paper, but I really don’t have the ability to use legitimate expression to express it by CVX. Is this a limitation of CVX?
Use pow_pos(norm(v(n)),3).
Wa, thank you very much. I still have a lot to learn 