The object function is

where X is a matrix of N by M, and n is the row index, so Xn denotes the n-th row of X. g() denotes the hyperbolic tangent function (tanh). Since the X is optimized iteratively, so the value being not relevant to X is calculated out of the {cvx_begin…cvx_end} and passed in the {cvx_begin…cvx_end} as constants (constant vectors). The problem is how can I express the square of norms of each row of X? The code is as follows:

```
Qx1=constant_vector1;
Qx21 =constant_vector2;
Qx22 = constant_vector3;
cvx_begin quiet
variable x(N,M) complex
minimize(sum(Qx1+Qx21.*(norms(norms(X,2,2),2,1)-Qx22)));
subject to
norm(b - A*X,'fro') <= SNR_eps;
cvx_end
```

It reports the error:

```
Disciplined convex programming error:
Invalid computation: norms( {convex}, ... )
```

Would you please tell me the reason or provide another method to express correctly?

Regards!