DocumentCode :
807
Title :
Enhancing Synchronizability of Diffusively Coupled Dynamical Networks: A Survey
Author :
Jalili, Mahdi
Author_Institution :
Dept. of Comput. Eng., Sharif Univ. of Technol., Tehran, Iran
Volume :
24
Issue :
7
fYear :
2013
fDate :
Jul-13
Firstpage :
1009
Lastpage :
1022
Abstract :
In this paper, we review the literature on enhancing synchronizability of diffusively coupled dynamical networks with identical nodes. The last decade has witnessed intensive investigations on the collective behavior over complex networks and synchronization of dynamical systems is the most common form of collective behavior. For many applications, it is desired that the synchronizability-the ability of networks in synchronizing activity of their individual dynamical units-is enhanced. There are a number of methods for improving the synchronization properties of dynamical networks through structural perturbation. In this paper, we survey such methods including adding/removing nodes and/or edges, rewiring the links, and graph weighting. These methods often try to enhance the synchronizability through minimizing the eigenratio of the Laplacian matrix of the connection graph-a synchronizability measure based on the master-stability-function formalism. We also assess the performance of the methods by numerical simulations on a number of real-world networks as well as those generated through models such as preferential attachment, Watts-Strogatz, and Erdos-Rényi.
Keywords :
complex networks; eigenvalues and eigenfunctions; graph theory; matrix algebra; network theory (graphs); perturbation techniques; synchronisation; Erdos-Renyi model; Laplacian matrix; Watts-Strogatz model; adding nodes; collective behavior; complex networks; connection graph; diffusively coupled dynamical networks; dynamical systems; eigenratio; graph weighting; identical nodes; individual dynamical units; master-stability-function formalism; numerical simulations; preferential attachment; real-world networks; removing nodes; structural perturbation; synchronizability enhancement; synchronizability measure; synchronization property; synchronizing activity; Complex networks; dynamical systems; synchronizability enhancement; synchronization;
fLanguage :
English
Journal_Title :
Neural Networks and Learning Systems, IEEE Transactions on
Publisher :
ieee
ISSN :
2162-237X
Type :
jour
DOI :
10.1109/TNNLS.2013.2250998
Filename :
6490063
Link To Document :
بازگشت