variable coupling
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Author(s):  
Janarthanan Ramadoss ◽  
Karthikeyan Rajagopal ◽  
Hayder Natiq ◽  
Iqtadar Hussain

Abstract The master stability function (MSF) is an approach to evaluate the local stability of the synchronization in coupled oscillators. Computing the MSF of a network according to its parameters results in a curve whose shape is dependent on the nodes’ dynamics, network topology, coupling function, and coupling strength. This paper calculates the MSF of networks of two diffusively coupled oscillators by considering different single variable and multi-variable couplings. Then, the linearity of the MSF is investigated by fitting a straight line to the MSF curve, and the root mean square error is obtained. It is observed that the multi-variable coupling with equal coefficients on all variables results in a linear MSF regardless of the dynamics of the nodes.


Mathematics ◽  
2021 ◽  
Vol 9 (21) ◽  
pp. 2721
Author(s):  
Jian Zhu ◽  
Da Huang ◽  
Haijun Jiang ◽  
Jicheng Bian ◽  
Zhiyong Yu

The system model on synchronizability problem of complex networks with multi-layer structure is closer to the real network than the usual single-layer case. Based on the master stability equation (MSF), this paper studies the eigenvalue spectrum of two k-layer variable coupling windmill-type networks. In the case of bounded and unbounded synchronization domain, the relationships between the synchronizability of the layered windmill-type networks and network parameters, such as the numbers of nodes and layers, inter-layers coupling strength, are studied. The simulation of the synchronizability of the layered windmill-type networks are given, and they verify the theoretical results well. Finally, the optimization schemes of the synchronizability are given from the perspective of single-layer and multi-layer networks, and it was found that the synchronizability of the layered windmill-type networks can be improved by changing the parameters appropriately.


Pramana ◽  
2021 ◽  
Vol 95 (1) ◽  
Author(s):  
Yin Zhang ◽  
Ping Zhou ◽  
Zhao Yao ◽  
Jun Ma
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