Nonlinear problem

Hi,

I am trying to minimize a function like f(x)=H1x+H2x^2+H3x^3

Can we really do it using cvx toolbox, ifnot can you suggest any best available tools for the problem.

If `H1, H2, H3` are all input data (i.e., numbers) `>= 0` (`H1` need not be `>= 0`), you should be able to enter `f(x)` “as is” into CVX. Have you read the CVX Users’ Guide?

The H1,H2,H3 are the matrices made from the input data.

When writing higher powers of X, like X^2 etc I am getting disciplined program issue.

I was assuming that everything was scalars.

The first thing you need to do is to define s SCALAR objective function. That scalar function needs to be convex. If it is convex, it might be possible to use CVX, but not necessarily so.

If you have a scalar objective function, but it is not convex, you can consider using YALMIP. Until you have a scalar objective function, you are not ready to perform optimization.

Thank you, as mentioned X is a vector and H is a matrix.

If X is a vector, what is X^2 or X^3?

As I wrote above, the first thing you need to do is to define s SCALAR objective function.