Network Clustering for SISO Linear Dynamical Networks via Reaction-Di usion Transformation

Abstract In this paper, we study a network clustering problem for SISO linear dynamical networks. The proposed clustering method aggregates states which behave similarly for arbitrary input signals. We show that such states can efficiently be found via the Reaction-Diffusion transformation. The results give a model reduction procedure that preserves the stability and network structure.

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