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
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;
Conference_Titel :
Control Conference (CCC), 2015 34th Chinese
Conference_Location :
Hangzhou, China
DOI :
10.1109/ChiCC.2015.7259823
