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
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