High-order problem

Hi,
I am working on the N-dimensional time-series graphs. I wrote a CVX code to optimize a parameter where this parameter has the same dimension of the “number of nodes * number of times (observations)”.

When I run this code for a few numbers of nodes and times (eg N=4 and T=5) it works properly but when I increase them (eg N=50 and T 60) CVX cannot solve the problem and always reaches NaN.
Indeed I receive this message: Status: Infeasible
Optimal value (cvx_optval): +Inf

How can I increase the ability of CVX to solve high-order programs?

Thanks in advance

Show us the problem. Show us the solver and CVX output so we can see what manner of “failure” is occurring, for instance, out of memory, numerical difficulties for the solver, or the problem is infeasible.

Many thanks for your reply. You meant that I send the code here? because this is a 300 line code.

The error is :

Status: Infeasible
Optimal value (cvx_optval): +Inf

That says the problem is infeasible. Follow the advice at https://yalmip.github.io/debugginginfeasible/ , which also applies to CVX, other than some syntax differences.

Many thanks, surely I will do that