Observability of Nonlinear Complex Networks in the Presence of Symmetries: A Graphical Approach

TL;DR

This paper investigates how symmetries in nonlinear complex networks affect their observability and introduces an efficient algorithm to identify the minimal sensor set needed for state reconstruction.

Contribution

It provides a novel graphical method to analyze observability considering network symmetries and offers an algorithm to determine minimal sensor configurations.

Findings

Symmetries can hinder network observability.

The proposed algorithm efficiently finds minimal sensor sets.

The approach improves sensor placement strategies in complex networks.

Abstract

Reconstructing the states of the nodes of a dynamical network is a problem of fundamental importance in the study of neuronal and genetic networks. An underlying related problem is that of observability, i.e., identifying the conditions under which such a reconstruction is possible. In this paper we study observability of complex dynamical networks, where we consider the effects of network symmetries on observability. We present an efficient algorithm that returns a minimal set of necessary sensor nodes for observability in the presence of symmetries.