Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/55405
Title: Introducing robustness in controllability of neuronal networks
Authors: Tang, Y
Du, W
Keywords: Controllability
Multiobjective optimization
Neuronal networks
Robustness
Synchronization
Issue Date: 2015
Publisher: IEEE Computer Society
Source: Q Zhao & S Liu (Eds.), Proceedings of the 34th Chinese Control Conference : July 2015, Hongzhou, China, 7259823, p. 1309-1312 How to cite?
Abstract: This paper addresses robust multiobjective identification of driver nodes in the neuronal network of a cat's brain, in which uncertainties in determination of driver nodes and control gains are considered. A framework by including interval uncertainties is proposed for robust controllability. It is revealed that the existence of uncertainties in choosing driver nodes and designing control gains heavily affect the controllability of neuronal networks.
URI: http://hdl.handle.net/10397/55405
ISBN: 9789881563897
ISSN: 1934-1768
DOI: 10.1109/ChiCC.2015.7259823
Appears in Collections:Conference Paper

Access
View full-text via PolyU eLinks SFX Query
Show full item record

Page view(s)

19
Last Week
0
Last month
Checked on Sep 18, 2017

Google ScholarTM

Check

Altmetric



Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.