
TL;DR
This paper investigates the extent to which the structure of linear systems can be determined solely from input/output data, revealing fundamental limitations and the need for additional assumptions or domain knowledge.
Contribution
It demonstrates that input/output data alone often cannot uniquely identify a system's structure, highlighting the importance of assumptions and domain knowledge in structural identification.
Findings
Linear transformations can alter the system's graph.
Input/output behavior does not determine graph components.
Additional assumptions are necessary for structure identification.
Abstract
In this paper, we consider to what degree the structure of a linear system is determined by the system's input/output behavior. The structure of a linear system is a directed graph where the vertices represent the variables in the system and an edge (x,y) exists if x directly influences y. In a number of studies, researchers have attempted to identify such structures using input/output data. Thus, our main aim is to consider to what degree the results of such studies are valid. We begin by showing that in many cases, applying a linear transformation to a system will change the system's graph. Furthermore, we show that even the graph's components and their interactions are not determined by input/output behavior. From these results, we conclude that without further assumptions, very few aspects, if any, of a system's structure are determined by its input/output relation. We consider a…
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Taxonomy
TopicsComplex Network Analysis Techniques · Gene Regulatory Network Analysis · Advanced Software Engineering Methodologies
