  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.
