Dear Professor, I would like to ask you a question about CVX. The procedure is as follows：
The constraints of CVX are as follows：
In which β_1=norm((M_1*G+v_1),1),β_2=norm((M_2*G+v_2),1),
M_1,v_1,M_2,v_2 are variables in CVX, defined as follows:
I don’t know how to express the second-order norm constraint including the first-order norm in CVX. I hope you can help me,thanks
Have you proven this i s convex?
If β_1 is convex, the constrain is connvex
Please show us the proof.
Actually, I didn’t prove it, but I did program it to define β as a variable, not a first order norm, and it would run.i do not know it’s different
norm is not affine, so can’t be used in an argument of
Disciplined convex programming information:
norm is convex, except when P<1, so an error will result if
these non-convex “norms” are used within CVX expressions. norm
is nonmonotonic, so its input must be affine.
Please carefully read
What can be used to replace the first order norm? Can the Max function be used
You apparently have either not read or have not understood the link.