Dynamics of a multiplex neural network with delayed couplings

doi:10.1007/s10483-021-2709-6

摘要/Abstract

摘要： Multiplex networks have drawn much attention since they have been observed in many systems, e.g., brain, transport, and social relationships. In this paper, the nonlinear dynamics of a multiplex network with three neural groups and delayed interactions is studied. The stability and bifurcation of the network equilibrium are discussed, and interesting neural activities of the network are explored. Based on the neuron circuit, transfer function circuit, and time delay circuit, a circuit platform of the network is constructed. It is shown that delayed couplings play crucial roles in the network dynamics, e.g., the enhancement and suppression of the stability, the patterns of the synchronization between networks, and the generation of complicated attractors and multi-stability coexistence.

关键词: neural network, time delay, synchronization, coexisting attractor

Abstract: Multiplex networks have drawn much attention since they have been observed in many systems, e.g., brain, transport, and social relationships. In this paper, the nonlinear dynamics of a multiplex network with three neural groups and delayed interactions is studied. The stability and bifurcation of the network equilibrium are discussed, and interesting neural activities of the network are explored. Based on the neuron circuit, transfer function circuit, and time delay circuit, a circuit platform of the network is constructed. It is shown that delayed couplings play crucial roles in the network dynamics, e.g., the enhancement and suppression of the stability, the patterns of the synchronization between networks, and the generation of complicated attractors and multi-stability coexistence.

Key words: neural network, time delay, synchronization, coexisting attractor

中图分类号:

65D15

Xiaochen MAO, Xingyong LI, Weijie DING, Song WANG, Xiangyu ZHOU, Lei QIAO. Dynamics of a multiplex neural network with delayed couplings[J]. Applied Mathematics and Mechanics (English Edition), 2021, 42(3): 441-456.

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