scholarly journals Feedback pinning control of collective behaviors aroused by epidemic spread on complex networks

2019 ◽  
Vol 29 (3) ◽  
pp. 033122 ◽  
Author(s):  
Pan Yang ◽  
Zhongpu Xu ◽  
Jianwen Feng ◽  
Xinchu Fu
Keyword(s):  
Complex Networks ◽  
Pinning Control ◽  
Epidemic Spread ◽  
Collective Behaviors

scholarly journals Pinning control of complex networks with time-varying inner and outer coupling

2021 ◽  
Vol 18 (4) ◽  
pp. 3435-3447
Author(s):  
Hai Lin ◽  
◽  
Jingcheng Wang ◽  
◽  
Keyword(s):  
Complex Networks ◽  
Pinning Control ◽  
Time Varying

Analysis and Pinning Control for Output Synchronization and $\mathcal{H}_{\infty}$ Output Synchronization of Multiweighted Complex Networks

2019 ◽  
Vol 49 (4) ◽  
pp. 1314-1326 ◽  
Author(s):  
Jin-Liang Wang ◽  
Zhen Qin ◽  
Huai-Ning Wu ◽  
Tingwen Huang ◽  
Pu-Chong Wei
Keyword(s):  
Complex Networks ◽  
Pinning Control ◽  
Output Synchronization

scholarly journals Locating the Epidemic Source in Complex Networks with Sparse Observers

2019 ◽  
Vol 9 (18) ◽  
pp. 3644 ◽  
Author(s):  
Xiang Li ◽  
Xiaojie Wang ◽  
Chengli Zhao ◽  
Xue Zhang ◽  
Dongyun Yi
Keyword(s):  
Complex Networks ◽  
Source Localization ◽  
Disease Spread ◽  
Initial Time ◽  
Epidemic Spread ◽  
Localization Accuracy ◽  
General Network ◽  
Maximum Spanning Tree ◽  
Comparison Algorithms ◽  
Empirical Networks

Epidemic source localization is one of the most meaningful areas of research in complex networks, which helps solve the problem of infectious disease spread. Limited by incomplete information of nodes and inevitable randomness of the spread process, locating the epidemic source becomes a little difficult. In this paper, we propose an efficient algorithm via Bayesian Estimation to locate the epidemic source and find the initial time in complex networks with sparse observers. By modeling the infected time of observers, we put forward a valid epidemic source localization method for tree network and further extend it to the general network via maximum spanning tree. The numerical analyses in synthetic networks and empirical networks show that our algorithm has a higher source localization accuracy than other comparison algorithms. In particular, when the randomness of the spread path enhances, our algorithm has a better performance. We believe that our method can provide an effective reference for epidemic spread and source localization in complex networks.

scholarly journals Inverse optimal pinning control for synchronization of complex networks with nonidentical chaotic nodes

2018 ◽  
Vol 51 (13) ◽  
pp. 235-239
Author(s):  
Carlos J. Vega ◽  
Edgar N. Sanchez ◽  
Ricardo Alzate
Keyword(s):  
Complex Networks ◽  
Pinning Control
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