Effects of symmetry on the structural controllability of neural networks

A perspective

Andrew J. Whalen, Sean N. Brennan, Timothy D. Sauer, Steven Schiff

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The controllability of a dynamical system or network describes whether a given set of control inputs can completely exert influence in order to drive the system towards a desired state. Structural controllability develops the canonical coupling structures in a network that lead to un-controllability, but does not account for the effects of explicit symmetries contained in a network. Recent work has made use of this framework to determine the minimum number and location of the optimal actuators necessary to completely control complex networks. In systems or networks with structural symmetries, group representation theory provides the mechanisms for how the symmetry contained in a network will influence its controllability, and thus affects the placement of these critical actuators, which is a topic of broad interest in science from ecological, biological and man-made networks to engineering systems and design.

Original languageEnglish (US)
Title of host publication2016 American Control Conference, ACC 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages5785-5790
Number of pages6
ISBN (Electronic)9781467386821
DOIs
StatePublished - Jul 28 2016
Event2016 American Control Conference, ACC 2016 - Boston, United States
Duration: Jul 6 2016Jul 8 2016

Publication series

NameProceedings of the American Control Conference
Volume2016-July
ISSN (Print)0743-1619

Other

Other2016 American Control Conference, ACC 2016
CountryUnited States
CityBoston
Period7/6/167/8/16

Fingerprint

Controllability
Neural networks
Actuators
Complex networks
Systems engineering
Dynamical systems

All Science Journal Classification (ASJC) codes

  • Electrical and Electronic Engineering

Cite this

Whalen, A. J., Brennan, S. N., Sauer, T. D., & Schiff, S. (2016). Effects of symmetry on the structural controllability of neural networks: A perspective. In 2016 American Control Conference, ACC 2016 (pp. 5785-5790). [7526576] (Proceedings of the American Control Conference; Vol. 2016-July). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ACC.2016.7526576
Whalen, Andrew J. ; Brennan, Sean N. ; Sauer, Timothy D. ; Schiff, Steven. / Effects of symmetry on the structural controllability of neural networks : A perspective. 2016 American Control Conference, ACC 2016. Institute of Electrical and Electronics Engineers Inc., 2016. pp. 5785-5790 (Proceedings of the American Control Conference).
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Whalen, AJ, Brennan, SN, Sauer, TD & Schiff, S 2016, Effects of symmetry on the structural controllability of neural networks: A perspective. in 2016 American Control Conference, ACC 2016., 7526576, Proceedings of the American Control Conference, vol. 2016-July, Institute of Electrical and Electronics Engineers Inc., pp. 5785-5790, 2016 American Control Conference, ACC 2016, Boston, United States, 7/6/16. https://doi.org/10.1109/ACC.2016.7526576

Effects of symmetry on the structural controllability of neural networks : A perspective. / Whalen, Andrew J.; Brennan, Sean N.; Sauer, Timothy D.; Schiff, Steven.

2016 American Control Conference, ACC 2016. Institute of Electrical and Electronics Engineers Inc., 2016. p. 5785-5790 7526576 (Proceedings of the American Control Conference; Vol. 2016-July).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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Whalen AJ, Brennan SN, Sauer TD, Schiff S. Effects of symmetry on the structural controllability of neural networks: A perspective. In 2016 American Control Conference, ACC 2016. Institute of Electrical and Electronics Engineers Inc. 2016. p. 5785-5790. 7526576. (Proceedings of the American Control Conference). https://doi.org/10.1109/ACC.2016.7526576