Other details of this deep learning - based , data - driven design of diffractive layers are presented in the section " Image datasets and diffractive network training parameters " . After the training is over , which is a one - time effort , the estimate transformation matrix and the corresponding vectorized form , A′ and vec(A′ ) = a′ , are computed using the optimized neuron transmission values in Eq . 2 . After computing a′ , we also compute the normalization constant , m , which minimizes ‖a − ma′‖ 2 , resulting in :