期刊
CHAOS SOLITONS & FRACTALS
卷 153, 期 -, 页码 -出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.chaos.2021.111541
关键词
Spiking neuronal networks; Synchronization; Order parameter; Cluster synchronization; Chimera state; Travelling chimera state; Travelling wave
资金
- Basic Research Program at the National Research University Higher School of Economics
- ANR Project ERMUNDY [ANR-18-CE37-0014]
The study introduces a universal approach to identify multiple network dynamical states and automatically disambiguates synchronized clusters. The method exhibits robustness for different network structures, can determine the number of clusters in cluster synchronization scenarios, and is applicable to various relaxation oscillator networks.
We propose a robust universal approach to identify multiple network dynamical states, including stationary and travelling chimera states based on an adaptive coherence measure. Our approach allows automatic disambiguation of synchronized clusters, travelling waves, chimera states, and asynchronous regimes. In addition, our method can determine the number of clusters in the case of cluster synchronization. We further couple our approach with a new speed calculation method for travelling chimeras. We validate our approach by an example of a ring network of type II Morris-Lecar neurons with asymmetrical nonlocal inhibitory connections where we identify a rich repertoire of coherent and wave states. We propose that the method is robust for the networks of phase oscillators and extends to a general class of relaxation oscillator networks. (c) 2021 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license ( http://creativecommons.org/licenses/by-nc-nd/4.0/ )
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据