DocumentCode
2243397
Title
Introducing robustness in controllability of neuronal networks
Author
Yang, Tang ; Wei, Du
Author_Institution
The Key Laboratory of Advanced Control and Optimization for Chemical Processes, Ministry of Education, East China University of Science and Technology, Shanghai 200237, China
fYear
2015
fDate
28-30 July 2015
Firstpage
1309
Lastpage
1312
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.
Keywords
Biological neural networks; Complex networks; Controllability; Optimization; Robustness; Synchronization; Uncertainty; Controllability; Multiobjective optimization; Neuronal networks; Robustness; Synchronization;
fLanguage
English
Publisher
ieee
Conference_Titel
Control Conference (CCC), 2015 34th Chinese
Conference_Location
Hangzhou, China
Type
conf
DOI
10.1109/ChiCC.2015.7259823
Filename
7259823
Link To Document