  This paper studies reduced-order modeling of dynamic networks with strongly
connected topology. Given a graph clustering of an original complex network, we
construct a quotient graph with less number of vertices, where the edge weights
are parameters to be determined. The model of the reduced network is thereby
obtained with parameterized system matrices, and then an edge weighting
procedure is devised, aiming to select an optimal set of edge weights that
minimizes the approximation error between the original and the reduced-order
network models in terms of H2-norm. The effectiveness of the proposed method is
illustrated by a numerical example.
