Optimized network structure for full-synchronization

Carareto, Rodrigo; Orsatti, Fernando Moya; Piqueira, José Roberto Castilho

doi:10.1016/j.cnsns.2008.09.032

Cited by 21 publications

(16 citation statements)

References 26 publications

(37 reference statements)

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…The verification that synchronization is enhanced when nodes are surrounded by neighbors of the opposite frequency was also observed for networks presenting symmetric bipolar distribution of natural frequencies [330]. Carareto et al [342] also verified that this anti-correlation and degree homogeneity are not conflicting, proposing a solution for the heterogeneity paradox [133].…”

Section: Optimization Of Synchronizationmentioning

confidence: 67%

See 1 more Smart Citation

The Kuramoto model in complex networks

et al. 2016

View full text Add to dashboard Cite

Synchronization of an ensemble of oscillators is an emergent phenomenon present in several complex systems, ranging from social and physical to biological and technological systems. The most successful approach to describe how coherent behavior emerges in these complex systems is given by the paradigmatic Kuramoto model. This model has been traditionally studied in complete graphs. However, besides being intrinsically dynamical, complex systems present very heterogeneous structure, which can be represented as complex networks. This report is dedicated to review main contributions in the field of synchronization in networks of Kuramoto oscillators. In particular, we provide an overview of the impact of network patterns on the local and global dynamics of coupled phase oscillators. We cover many relevant topics, which encompass a description of the most used analytical approaches and the analysis of several numerical results. Furthermore, we discuss recent developments on variations of the Kuramoto model in networks, including the presence of noise and inertia. The rich potential for applications is discussed for special fields in engineering, neuroscience, physics and Earth science. Finally, we conclude by discussing problems that remain open after the last decade of intensive research on the Kuramoto model and point out some promising directions for future research.

show abstract

Section: Optimization Of Synchronizationmentioning

confidence: 67%

“…The topology optimization of a network of non-identical oscillators was also studied by Carareto et al [342]. Their main goal was to obtain a complete synchronization with the smallest possible coupling strength λ.…”

Section: Optimization Of Synchronizationmentioning

confidence: 99%

The Kuramoto model in complex networks

et al. 2016

View full text Add to dashboard Cite

show abstract

“…Besides, in [22], some hints about optimizing synchronization parameters considering topology changes are presented.…”

Section: Neural Models and Time Signal Processingmentioning

confidence: 99%

Network of phase-locking oscillators and a possible model for neural synchronization

Piqueira

2011

Communications in Nonlinear Science and Numerical Simulation

View full text Add to dashboard Cite

“…However, we disregard the need for any particular distribution of the oscillator's natural frequencies [34][35][36] and the need for any particular coupling function, , or topology, W [37][38][39][40]. Consequently, our PMSF framework and results are general and applicable to any network of phase-oscillators.…”

Section: Pmsf General Implicationsmentioning

confidence: 93%

Synchronisation

Rubido

2015

Energy Transmission and Synchronization in Complex Networks

View full text Add to dashboard Cite

Optimized network structure for full-synchronization

Cited by 21 publications

References 26 publications

The Kuramoto model in complex networks

The Kuramoto model in complex networks

Network of phase-locking oscillators and a possible model for neural synchronization

Synchronisation

Contact Info

Product

Resources

About