时间：12.24 15：30-17：00

地点：信息大楼C310

Title: Toward Stronger Robustness of Network Controllability

Abstract:

A new complex network model, called q-snapback network, is introduced. Basic topological characteristics of the network, such as degree distribution, average path length, clustering coefficient and Pearson correlation coefficient, are evaluated. The typical 3- and 4-motifs of the network are simulated. The robustness of both state and structural controllabilities of the network against targeted and random node- and edge-removal attacks, with comparisons to the multiplex congruence network, the generic scale-free and random-graph networks and some other network topologies, are presented. It is shown that the q-snapback network has the strongest robustness of controllabilities due to its advantageous inherent structure with many chain- and loop-motifs.

Brief Bio:

Dr. Yang Lou received the Ph.D. degree from Department of Electronic Engineering, City University of Hong Kong, Hong Kong SAR, China, in 2017, where he has been a Postdoctoral Fellow since October 2017. Before that, he received the B.E. degree in Electrical Information Engineering from Xidian University, China, in 2008, and M.S. degree in Computer Science from Ningbo University, China, in 2012.  His current research interests include evolutionary computation, artificial intelligence and complex networks.