Chapter 10

Structure Identification for Networked Systems

Abstract

In this chapter, we discuss how to infer subsystem interactions in a networked system from experimental data. This problem is of particular importance in fields like systems biology, financial engineering, and so on. It appears also helpful in attack preventions for a networked system. Particular attention is given to the structure inference for a gene regulatory network. We consider two situations. One is on the basis of steady-state experimental data, and the other is on the basis of dynamic or time series experimental data. Sparsity of a large-scale networked system is also taken into account in these investigations. Based on the total least square estimations and robust ...

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