In this note, we will present a specially designed deep neural network (DNN), which will target components of the solution of different time rate individually through perspective of the Laplace s-transform of the solution. Each segment of s-frequency range will be approximated by a small size DNN separately after a reference central rate is factored out, leaving the rest of the frequencies confined within a short range of rates, and allowing fast and uniform learning by normal DNN.