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Inferring Network Connectivity by Delayed Feedback Control

Authors
Journal
PLoS ONE
1932-6203
Publisher
Public Library of Science
Publication Date
Volume
6
Issue
9
Identifiers
DOI: 10.1371/journal.pone.0024333
Keywords
  • Research Article
  • Biology
  • Computational Biology
  • Cryobiology
  • Systems Biology
  • Theoretical Biology
  • Mathematics
  • Applied Mathematics
  • Complex Systems
  • Nonlinear Dynamics
  • Physics
  • Interdisciplinary Physics
Disciplines
  • Computer Science
  • Mathematics

Abstract

We suggest a control based approach to topology estimation of networks with elements. This method first drives the network to steady states by a delayed feedback control; then performs structural perturbations for shifting the steady states times; and finally infers the connection topology from the steady states' shifts by matrix inverse algorithm () or -norm convex optimization strategy applicable to estimate the topology of sparse networks from perturbations. We discuss as well some aspects important for applications, such as the topology reconstruction quality and error sources, advantages and disadvantages of the suggested method, and the influence of (control) perturbations, inhomegenity, sparsity, coupling functions, and measurement noise. Some examples of networks with Chua's oscillators are presented to illustrate the reliability of the suggested technique.

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