cvx_begin variable S(LEN_ANG,K); SSV = S*V1*Dk; minimize( norm(YSV - Aa*SSV) ); subject to sqrt(diag(SSV*SSV')) <= 0.1 cvx_end
It throws an error saying “Disciplined convex programming error:
Only scalar quadratic forms can be specified in CVX”…
My idea Here is minimize( norm(YSV - AaSSV) ) w.r.t SSV and I was using this **sqrt(diag(SSVSSV’))** to ensure sparsity only in columns.
Here YSV ,Aa and SSV all are Matrices.
Pls help anybody…Thanks in advance