Why Optimal value (cvx_optval): NaN

[Mark_L_Stone]

Yes, try to get the elements of `H’ to be close to magnitude 1.

I think that you need adequate scaling of everything else so that 1e-5, or maybe 1e-6 is adequate to ensure you get the strict nonnegativity you need in that constraint… Your other option is to adjust the solution from CVX prior to feeding them into your next iteration.

If you use SCA. there may be a risk that even if the 1st SCA iteration is well-scaled, some later iteration may not be. See

Algorithm cannot converge

SCA is generally unreliable, and might not converge to anything, let alone a global or even local optimum of the original problem. You should try to improve numerical scaling of input data, for instance by changing units, so that all non-zero input data is within a small number of orders of magnitude of 1. That might help your overall SCA performance, but not necessarily. Different (better) initialization values for the “SCA” variables might help, but not necessarily.