Estimating topology of networks.
We suggest a method for estimating the topology of a network based on the dynamical evolution supported on the network. Our method is robust and can be also applied when disturbances and/or modeling errors are presented. Several examples with networks of phase oscillators, pulse-coupled Hindmarch-Rose neurons, and Lorenz oscillators are provided to illustrate our approach.
Yu
Dongchuan
D
College of Automation Engineering, Qingdao University, 308 Ningxia Road, Qingdao, Shandong 266071, People's Republic of China.
Righero
Marco
M
Kocarev
Ljupco
L