Literature DB >> 16486704

Universality in the synchronization of weighted random networks.

Changsong Zhou1, Adilson E Motter, Jürgen Kurths.   

Abstract

Realistic networks display not only a complex topological structure, but also a heterogeneous distribution of weights in the connection strengths. Here we study synchronization in weighted complex networks and show that the synchronizability of random networks with a large minimum degree is determined by two leading parameters: the mean degree and the heterogeneity of the distribution of node's intensity, where the intensity of a node, defined as the total strength of input connections, is a natural combination of topology and weights. Our results provide a possibility for the control of synchronization in complex networks by the manipulation of a few parameters.

Year:  2006        PMID: 16486704     DOI: 10.1103/PhysRevLett.96.034101

Source DB:  PubMed          Journal:  Phys Rev Lett        ISSN: 0031-9007            Impact factor:   9.161


  11 in total

1.  Network synchronization landscape reveals compensatory structures, quantization, and the positive effect of negative interactions.

Authors:  Takashi Nishikawa; Adilson E Motter
Journal:  Proc Natl Acad Sci U S A       Date:  2010-05-20       Impact factor: 11.205

2.  Various synchronous states due to coupling strength inhomogeneity and coupling functions in systems of coupled identical oscillators.

Authors:  Junhyeok Kim; Joon-Young Moon; Uncheol Lee; Seunghwan Kim; Tae-Wook Ko
Journal:  Chaos       Date:  2019-01       Impact factor: 3.642

3.  Emergence of structural patterns out of synchronization in networks with competitive interactions.

Authors:  Salvatore Assenza; Ricardo Gutiérrez; Jesús Gómez-Gardeñes; Vito Latora; Stefano Boccaletti
Journal:  Sci Rep       Date:  2011-09-21       Impact factor: 4.379

4.  Matching rules for collective behaviors on complex networks: optimal configurations for vibration frequencies of networked harmonic oscillators.

Authors:  Meng Zhan; Shuai Liu; Zhiwei He
Journal:  PLoS One       Date:  2013-12-26       Impact factor: 3.240

5.  Synchronization in networks with multiple interaction layers.

Authors:  Charo I Del Genio; Jesús Gómez-Gardeñes; Ivan Bonamassa; Stefano Boccaletti
Journal:  Sci Adv       Date:  2016-11-16       Impact factor: 14.136

6.  Alzheimer's Disease Early Diagnosis Using Manifold-Based Semi-Supervised Learning.

Authors:  Moein Khajehnejad; Forough Habibollahi Saatlou; Hoda Mohammadzade
Journal:  Brain Sci       Date:  2017-08-20

7.  Network structure reveals patterns of legal complexity in human society: The case of the Constitutional legal network.

Authors:  Bokwon Lee; Kyu-Min Lee; Jae-Suk Yang
Journal:  PLoS One       Date:  2019-01-23       Impact factor: 3.240

8.  SimNet: Similarity-based network embeddings with mean commute time.

Authors:  Moein Khajehnejad
Journal:  PLoS One       Date:  2019-08-15       Impact factor: 3.240

9.  Identifying controlling nodes in neuronal networks in different scales.

Authors:  Yang Tang; Huijun Gao; Wei Zou; Jürgen Kurths
Journal:  PLoS One       Date:  2012-07-27       Impact factor: 3.240

10.  Graph theoretical analysis of complex networks in the brain.

Authors:  Cornelis J Stam; Jaap C Reijneveld
Journal:  Nonlinear Biomed Phys       Date:  2007-07-05
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