Literature DB >> 20481806

Effect of node-degree correlation on synchronization of identical pulse-coupled oscillators.

M Drew LaMar1, Gregory D Smith.   

Abstract

We explore the effect of correlations between the in and out degrees of random directed networks on the synchronization of identical pulse-coupled oscillators. Numerical experiments demonstrate that the proportion of initial conditions resulting in a globally synchronous state (prior to a large but finite time) is an increasing function of node-degree correlation. For those networks observed to globally synchronize, both the mean and standard deviation of time to synchronization are decreasing functions of node-degree correlation. Pulse-coupled oscillator networks with negatively correlated node degree often exhibit multiple coherent attracting states, with trajectories performing fast transitions between them. These effects of node-degree correlation on dynamics of pulse-coupled oscillators are consistent with aspects of network topology (e.g., the effect of node-degree correlation on the eigenvalues of the Laplacian matrix) that have been shown to affect synchronization in other contexts.

Mesh:

Year:  2010        PMID: 20481806     DOI: 10.1103/PhysRevE.81.046206

Source DB:  PubMed          Journal:  Phys Rev E Stat Nonlin Soft Matter Phys        ISSN: 1539-3755


  6 in total

1.  Strongly nonlinear dynamics of ferroelectric liquid crystals.

Authors:  W Jeżewski; I Sliwa; W Kuczyński
Journal:  Eur Phys J E Soft Matter       Date:  2013-01-15       Impact factor: 1.890

2.  Dynamics of Structured Networks of Winfree Oscillators.

Authors:  Carlo R Laing; Christian Bläsche; Shawn Means
Journal:  Front Syst Neurosci       Date:  2021-02-10

3.  The role of degree distribution in shaping the dynamics in networks of sparsely connected spiking neurons.

Authors:  Alex Roxin
Journal:  Front Comput Neurosci       Date:  2011-03-08       Impact factor: 2.380

4.  Synchronization from second order network connectivity statistics.

Authors:  Liqiong Zhao; Bryce Beverlin; Theoden Netoff; Duane Q Nykamp
Journal:  Front Comput Neurosci       Date:  2011-07-08       Impact factor: 2.380

5.  Simultaneous stability and sensitivity in model cortical networks is achieved through anti-correlations between the in- and out-degree of connectivity.

Authors:  Juan C Vasquez; Arthur R Houweling; Paul Tiesinga
Journal:  Front Comput Neurosci       Date:  2013-11-07       Impact factor: 2.380

6.  A permutation method for network assembly.

Authors:  Shawn A Means; Christian Bläsche; Carlo R Laing
Journal:  PLoS One       Date:  2020-10-23       Impact factor: 3.240

  6 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.