Hello everyone,
I am trying to solve the following optimisation problem
\begin{array}{l}
\min \left| x \right| _2 \
\text{subject to} \left| A x \right|_2 = \left| A \right|_2
\end{array}
where x \in \mathbb{R}^N, N \in \mathbb{N} , and A \in \mathbb{R}^{N \times N}.
I code it in cvx as
cvx_begin
variable x(length(A));
minimize (norm(x,2));
subject to
norm (A*x,2)==norm (A,2);
cvx_end
and I get the following error
error using ==> cvxprob.newcnstr at 192
Disciplined convex programming error:
Invalid constraint: {convex} == {real constant}
Is there anyway to overcome this error so I can solve the problem with cvx? can it be rewritten in another way so cvx can deal with it?
Sorry if it is a quite naive question, I am just learning about convex optimisation and cvx.
Thanks in advance.
Clemente